River and lake health evaluation method, standard determination method, system, device and medium

Abstract

The embodiment of the application provides a river and lake health evaluation method, a standard determination method, a system, equipment and a medium, and belongs to the technical field of data processing. The method comprises the following steps: acquiring a water inflow time sequence of a target river and lake, the water inflow time sequence comprising water inflows in multiple unit times; performing size sorting on the water inflows in the water inflow time sequence to obtain a water inflow sorting sequence; dividing the water inflow sorting sequence to determine multiple water inflow sub-sequences; for each water inflow sub-sequence, acquiring an index value corresponding to a unit time to which each water inflow in the water inflow sub-sequence belongs, and forming an index sub-sequence according to the index values; constructing a corresponding threshold sequence according to the index sub-sequence; and performing inspection on each element in the threshold sequence to determine a target evaluation standard of the corresponding water inflow sub-sequence. The application can improve the accuracy of the river and lake health evaluation standard and improve the reliability of the river and lake health evaluation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a river and lake health evaluation method, a standard determination method, a system, a device and a medium. BACKGROUND

[0002] Carrying out river and lake health evaluation is a necessary measure to master the health status of rivers and lakes, scientifically analyze river and lake problems, improve the level of river and lake governance and protection, and promote the construction of water ecological civilization. River and lake health evaluation can be evaluated from water quality, biomass and other indicators. Clear evaluation standards of evaluation indicators can provide an objective and quantifiable discrimination scale for the health status of rivers and lakes, help to ensure the consistency and comparability of the evaluation results, and enhance the public's awareness of river and lake health. At present, the evaluation standards of river and lake health indicators are generally determined based on artificial experience, and the determination of the evaluation standards is greatly influenced by human subjective factors. In addition, in the process of determining the evaluation standards, the water environment and water ecological chain reaction caused by the difference in inflow are not considered, and the health evaluation standards of rivers and lakes cannot adapt to different water flow variation conditions, resulting in inaccurate evaluation results. SUMMARY

[0003] The main purpose of the embodiments of the present application is to propose a river and lake health evaluation method, a standard determination method, a system, a device and a medium, which aims to improve the accuracy of the river and lake health evaluation standards and improve the reliability of the river and lake health evaluation.

[0004] To achieve the above-mentioned purpose, one aspect of the embodiments of the present application proposes a river and lake health evaluation standard determination method, comprising the following steps:

[0005] Obtain the inflow time series of the target river and lake, wherein the inflow time series includes the inflow in multiple unit times;

[0006] Sort the inflow in the inflow time series by size to obtain an inflow sorting sequence;

[0007] Divide the inflow sorting sequence to determine multiple inflow sub-sequences;

[0008] Obtain the index value corresponding to the unit time to which each inflow in the inflow sub-sequence belongs, and form an index sub-sequence according to each index value;

[0009] According to the index sub-sequence, a corresponding threshold sequence is constructed, and each element in the threshold sequence is tested to determine the target evaluation standard of the corresponding inflow sub-sequence, wherein each element of the threshold sequence represents a candidate evaluation standard.

[0010] In some embodiments, the dividing of the inflow sorting sequence to determine multiple inflow sub-sequences comprises the following steps:

[0011] calculating a design frequency of the incoming water quantity according to a number corresponding to each of the incoming water quantities in the incoming water quantity sequence;

[0012] dividing the incoming water quantities in the incoming water quantity sequence according to a preset division range of the design frequency to obtain a plurality of incoming water quantity sub-sequences.

[0013] In some embodiments, the dividing the design frequency of the incoming water quantity sequence according to the division range of the design frequency to obtain a plurality of incoming water quantity sub-sequences comprises the following steps:

[0014] performing curve fitting on each of the incoming water quantities in the incoming water quantity sequence and the corresponding design frequency to obtain a theoretical frequency curve;

[0015] dividing the incoming water quantities in the theoretical frequency curve according to a preset division range of the design frequency to obtain a plurality of incoming water quantity sub-sequences.

[0016] In some embodiments, the constructing a corresponding threshold sequence according to the index sub-sequence and performing inspection on each element in the threshold sequence to determine a target evaluation standard of the corresponding incoming water quantity sub-sequence comprises the following steps:

[0017] constructing a threshold sequence according to a preset step size with zero as a lower limit and a maximum index value in the index sub-sequence as an upper limit;

[0018] selecting an element in the threshold sequence as a to-be-inspected standard;

[0019] screening out an to-be-inspected sequence from the index sub-sequence with index values greater than the to-be-inspected standard;

[0020] performing inspection on a data distribution of the to-be-inspected sequence, and when the to-be-inspected sequence passes the inspection, determining the to-be-inspected standard as the target evaluation standard of the corresponding incoming water quantity sub-sequence; when the to-be-inspected sequence fails the inspection, selecting a next element in the threshold sequence as the to-be-inspected standard, and repeating the steps of screening out the to-be-inspected sequence from the index sub-sequence with index values greater than the to-be-inspected standard to performing inspection on the data distribution of the to-be-inspected sequence.

[0021] In some embodiments, the performing inspection on the data distribution of the to-be-inspected sequence comprises the following steps:

[0022] calculating a sequence fitting degree of the to-be-inspected sequence and an optimal distribution function by using K-S inspection to obtain a sequence fitting degree;

[0023] when the sequence fitting degree is greater than an expected fitting degree, determining that the to-be-inspected sequence passes the inspection;

[0024] When the sequence fitness is less than or equal to the expected fitness, it is determined that the sequence to be tested fails the test.

[0025] In some embodiments, the optimal distribution function of the index sub-sequence is determined by the following steps:

[0026] Obtaining a plurality of candidate distribution functions;

[0027] Calculating the information entropy and the partial entropy between the index sub-sequence and the candidate distribution function, and calculating the correlation coefficient between the index sub-sequence and the candidate distribution function according to the information entropy and the partial entropy;

[0028] Selecting the candidate distribution function with the largest correlation coefficient with the index sub-sequence as the optimal distribution function of the index sub-sequence.

[0029] To achieve the above object, another aspect of the embodiment of the present application proposes a method for evaluating the health of a river or lake, comprising the following steps:

[0030] Obtaining target evaluation data of a target river or lake, wherein the target evaluation data comprises a target inflow and a target index value;

[0031] Obtaining an inflow range of each inflow sub-sequence, and determining the corresponding inflow sub-sequence according to the inflow range to which the target inflow belongs, and obtaining the corresponding target evaluation standard according to the inflow sub-sequence; wherein the target evaluation standard is determined by the method for determining the health evaluation standard of a river or lake described in the above embodiment;

[0032] Analyzing the target index value according to the target evaluation standard to obtain a health evaluation result of the river or lake.

[0033] To achieve the above object, another aspect of the embodiment of the present application proposes a system for determining the health evaluation standard of a river or lake, comprising:

[0034] A first module for obtaining an inflow time sequence of a target river or lake, wherein the inflow time sequence comprises the inflow in a plurality of unit times;

[0035] A second module for sorting the inflow in the inflow time sequence by size to obtain an inflow sorting sequence;

[0036] A third module for dividing the inflow sorting sequence to determine a plurality of inflow sub-sequences;

[0037] A fourth module for obtaining an index value corresponding to each unit time to which the inflow in each inflow sub-sequence belongs, and forming an index sub-sequence according to each index value;

[0038] A fifth module configured to construct a corresponding threshold sequence according to the index sub-sequence, and to perform a test on each element in the threshold sequence to determine a target evaluation criterion of the corresponding water inflow sub-sequence, wherein each element of the threshold sequence represents a candidate evaluation criterion.

[0039] To achieve the above object, another aspect of the embodiments of the present application provides an electronic device, which comprises a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection communication between the processor and the memory, and the program is executed by the processor to realize the method described in the above embodiments.

[0040] To achieve the above object, another aspect of the embodiments of the present application provides a storage medium, which is a computer readable storage medium for computer readable storage, and the storage medium stores one or more programs, and the one or more programs are executable by one or more processors to realize the method described in the above embodiments.

[0041] The river and lake health evaluation method, the standard determination method, the system, the device and the medium provided by the present application obtain the water inflow time sequence of the target river and lake, the water inflow time sequence comprises water inflows in multiple unit times, the water inflows in the water inflow time sequence are sorted to obtain a water inflow sorting sequence, the water inflow sorting sequence is divided to determine multiple water inflow sub-sequences, for each water inflow sub-sequence, the index value corresponding to the unit time to which each water inflow belongs is obtained, and an index sub-sequence is formed according to the index values, then a corresponding threshold sequence is constructed according to the index sub-sequence, and each element in the threshold sequence is tested to determine the target evaluation criterion of the corresponding water inflow sub-sequence. The present application considers the variation of the water inflow in the historical data, divides the historical data based on the water inflow, and determines the appropriate target evaluation criterion in the respective water inflow range through the threshold test method, improves the accuracy of the river and lake health evaluation standard in each water inflow range, and thus improves the reliability of the river and lake health evaluation. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 is a flowchart of the river and lake health evaluation standard determination method provided by the embodiments of the present application;

[0043] Figure 2 is a flowchart of the river and lake health evaluation method provided by the embodiments of the present application;

[0044] Figure 3 is a schematic diagram of a theoretical frequency curve provided by the embodiments of the present application;

[0045] Figure 4 is a schematic diagram of the hardware structure of the electronic device provided by the embodiments of the present application. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0047] It should be noted that although the system is divided into functional modules and the flowchart shows a logical order, in some cases, the steps shown or described may be executed in a different order than the module division in the system or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0049] Conducting river and lake health assessments is a necessary measure to understand the health status of rivers and lakes, scientifically analyze river and lake problems, improve the level of river and lake management and protection, and promote the construction of water ecological civilization. Clearly defined evaluation criteria provide an objective and quantifiable scale for judging the health status of rivers and lakes, helping to ensure the consistency and comparability of evaluation results and enhancing public awareness of river and lake health. Among related technologies, the determination of evaluation criteria generally involves the following methods:

[0050] The empirical method relies on the experience accumulated by experts and practitioners over long-term work or research to determine evaluation criteria. This method is suitable for situations with a mature practical foundation and relatively unified opinions among experts in the field. However, evaluation criteria are easily affected by the limitations of personal experience and subjective biases, leading to significant differences.

[0051] Statistical analysis determines evaluation criteria by calculating statistical parameters of evaluation indicators. Representative statistical parameters include mean-standard deviation and quantiles. This method is suitable for scenarios with sufficient data, a sound data foundation, and certain regularities.

[0052] Machine learning methods leverage the powerful data feature learning capabilities of algorithms such as cluster analysis (K-Means clustering, hierarchical clustering, etc.) and deep learning (convolutional neural networks, recurrent neural networks, etc.) to analyze the potential structure of evaluation indicators and determine evaluation criteria. This method is suitable for complex, high-dimensional, and nonlinear data analysis scenarios, but it still requires manual setting or judgment of the rationality of the evaluation criteria level division.

[0053] The fuzzy comprehensive evaluation method converts the fuzzy evaluation into quantitative evaluation by establishing the membership function corresponding to the fuzzy evaluation index, so as to determine the evaluation standard. This method is applicable to social sciences, humanities management and other fields. The evaluation standard is easily disturbed by human subjective factors, and it is difficult to accurately grasp the change rule of the membership function of the evaluation index.

[0054] The above methods all evaluate the overall sample of the evaluation index as the object, without considering the influence of water difference on river health. Water resources are an important basis for supporting the sustainable development of river health, and water difference has a huge impact on river health. The above methods still use the same standard under the condition of water quantity change, without considering the river water environment and water ecological chain reaction caused by water difference to determine the evaluation standard, resulting in low reliability of river and lake health evaluation results.

[0055] In addition, the above methods are greatly influenced by human subjective factors, and there is no method for determining the evaluation standard based on the self-adaptation of river natural endowment. The experience method, machine learning method and fuzzy comprehensive evaluation method need to artificially define the evaluation standard and evaluation grade; the selection of statistical parameters in the statistical analysis method has strong subjectivity and directly affects the evaluation standard, also resulting in low reliability of river and lake health evaluation results.

[0056] Therefore, the embodiments of the present application provide a river and lake health evaluation method, a standard determination method, a system, a device and a medium, which aims to improve the accuracy of the river and lake health evaluation standard and improve the reliability of the river and lake health evaluation.

[0057] The river and lake health evaluation method, the standard determination method, the system, the device and the medium provided by the embodiments of the present application are specifically described as follows. First, the river and lake health evaluation standard determination method and the river and lake health evaluation method in the embodiments of the present application are described.

[0058] The river and lake health evaluation standard determination method and the river and lake health evaluation method provided by the embodiments of the present application are related to the technical field of data processing. The river and lake health evaluation standard determination method and the river and lake health evaluation method provided by the embodiments of the present application can be applied in a terminal, can be applied in a server side, and can also be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc.; the server side can be configured as a separate physical server, can be configured as a server cluster or a distributed system composed of multiple physical servers, can also be configured as a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN and basic cloud computing services such as big data and artificial intelligence platforms; the software can be an application for implementing the river and lake health evaluation standard determination method or the river and lake health evaluation method, but is not limited to the above forms.

[0059] The application is operable in a multitude of generic or specific computer system environments or configurations. Examples of well known computing systems, environments, and / or configurations that can be suitable for use with the application include personal computers, server computers, handheld or laptop devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application can be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like, that perform particular tasks or implement particular abstract data types. The application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules can be located in local and remote computer storage media including memory storage devices.

[0060] Figure 1 is an optional flowchart of a method for determining a river and lake health evaluation standard provided by an embodiment of the application, Figure 1 The method in the method can include but is not limited to including steps S101 to S106.

[0061] Step S101, acquiring a time sequence of inflow of a target river and lake, wherein the time sequence of inflow includes inflow in a plurality of unit times;

[0062] Step S102, sorting the inflow in the time sequence of inflow by size to obtain an inflow sorting sequence;

[0063] Step S103, dividing the inflow sorting sequence to determine a plurality of inflow sub-sequences;

[0064] Step S104, acquiring an index value corresponding to a unit time to which each inflow in the inflow sub-sequence belongs, and forming an index sub-sequence according to each index value;

[0065] Step S105, constructing a corresponding threshold sequence according to the index sub-sequence, and verifying each element in the threshold sequence to determine a target evaluation standard of the corresponding inflow sub-sequence, wherein each element of the threshold sequence represents a candidate evaluation standard.

[0066] In step S101 of some embodiments, the target river and lake refers to a lake that needs to be analyzed for health. The time sequence of inflow includes the inflow of the river and lake in a plurality of unit times that are continuous in time, and the unit time is set according to the needs, generally in units of "years". Illustratively, the annual average inflow of a certain river and lake from 1961 to 2022 is acquired, thereby forming the time sequence of inflow.

[0067] In step S102 of some embodiments, the inflow amount data in the inflow amount time sequence is sorted in chronological order. In this embodiment, the inflow amount data in the sequence is sorted according to the size of the inflow amount. Specifically, the annual inflow amount in the inflow amount time sequence can be sorted in descending order, or the annual inflow amount in the inflow amount time sequence can be sorted in ascending order, to obtain an inflow amount sorted sequence.

[0068] In step S103 of some embodiments, the inflow amount sorted sequence is divided according to a certain data amount proportion, to obtain a plurality of inflow amount sub-sequences, each corresponding to a corresponding inflow amount range. For example, the annual inflow amount in the inflow amount time sequence is sorted in descending order to obtain an inflow amount sorted sequence, and then the data amount of 100 of the inflow amount sorted sequence is divided into three inflow amount sub-sequences according to data amount proportions of 50%, 25%, and 25%, and the data amounts of the three inflow amount sub-sequences are 50, 25, and 25, respectively.

[0069] In some embodiments, the step of dividing the inflow amount sorted sequence to determine a plurality of inflow amount sub-sequences in step S103 can include, but is not limited to, the following steps:

[0070] Step S201, calculating the design frequency of the inflow amount according to the number corresponding to each inflow amount in the inflow amount sorted sequence;

[0071] Step S202, dividing the inflow amount of the inflow amount sorted sequence according to a preset division range of the design frequency, to obtain a plurality of inflow amount sub-sequences.

[0072] In this embodiment, the inflow amount time sequence Q(t) is arranged in descending order, where the inflow amount data is numbered from large to small as n = 1, 2, …, N, to obtain an inflow amount sorted sequence. Then the design frequency corresponding to each inflow amount in the inflow amount sorted sequence is calculated by the following formula:

[0073]

[0074] Where n represents the number of the inflow amount in the inflow amount sorted sequence, and N represents the total data number of the inflow amount sorted sequence.

[0075] The preset division range of the design frequency is defined as P <= 25%, 25% < P <= 50%, 50% < P <= 75%, 75% < P <= 90%, and 90% < P. It can be understood that the preset division range is only exemplary, and the preset division range can be set according to actual needs.

[0076] According to the division range of the design frequency, the inflow quantity in the inflow quantity sorting sequence can be divided, that is, the inflow quantity with a design frequency P<=25% in the inflow quantity sorting sequence is divided into a group, the inflow quantity with a design frequency belonging to 25%<P<=50% is divided into a group, the inflow quantity with a design frequency belonging to 50%<P<=75% is divided into a group, the inflow quantity with a design frequency belonging to 75%<P<=90% is divided into a group, and the inflow quantity with a design frequency belonging to 90%<P is divided into a group, so as to divide the inflow quantity sorting sequence into five inflow quantity sub-sequences. Further, since the inflow quantity sub-sequence with P>90% corresponds to a year belonging to a special dry year, the river and lake health status may need to be analyzed separately in actual evaluation, and is not included in the evaluation standard analysis range, that is, the inflow quantity sub-sequence with P>90% of Q(t) can be temporarily not analyzed.

[0077] In this embodiment, the inflow quantity is divided based on the design frequency, which can reduce the uncertainty caused by subjective factors compared with direct division based on experience, and improve the rationality of the division of the inflow quantity difference.

[0078] In some embodiments, the step of dividing the design frequency of the inflow quantity sorting sequence according to the division range of the design frequency in step S202 can include but is not limited to the following steps:

[0079] In step S301, a theoretical frequency curve is obtained by curve fitting of each inflow quantity in the inflow quantity sorting sequence and the corresponding design frequency.

[0080] In step S302, the inflow quantity of the theoretical frequency curve is divided according to the preset division range of the design frequency, to obtain a plurality of inflow quantity sub-sequences.

[0081] In this embodiment, after the design frequency of each inflow quantity in the inflow quantity sorting sequence is calculated, curve fitting of each inflow quantity in the inflow quantity sorting sequence is performed to calculate a theoretical frequency curve. The theoretical frequency curve is helpful to evaluate the occurrence probability of different magnitude inflow quantities. By fitting the inflow quantity and the design frequency into the theoretical frequency curve and then dividing the inflow quantity, the accuracy of the inflow quantity range corresponding to each inflow quantity sub-sequence can be improved, thereby improving the accuracy of subsequent evaluation. Exemplarily, the P-III type hydrological frequency analysis software with fitting degree calculation can be used to realize curve fitting, that is, the inflow quantity in the above-mentioned inflow quantity sorting sequence and the corresponding design frequency are input into the software to obtain the theoretical frequency curve. Then, the inflow quantity of the theoretical frequency curve is divided according to the preset division range to obtain a plurality of inflow quantity sub-sequences.

[0082] In step S104 of some embodiments, after the different water inflow sub-sequences are divided, for each water inflow sub-sequence, each water inflow data in the water inflow sub-sequence corresponds to a unit time, and according to actual evaluation requirements (for example, evaluation requirements of indexes such as oxygen content and organic matter content of rivers and lakes), an index value of the target river and lake in the unit time can be obtained, so as to obtain an index sub-sequence corresponding to the water inflow sub-sequence.

[0083] In step S105 of some embodiments, after the index sub-sequence corresponding to the water inflow sub-sequence is obtained, a threshold sequence corresponding to the index sub-sequence is constructed, each element of the threshold sequence represents a candidate evaluation standard with respect to the evaluation requirements, and each element in the threshold sequence is tested to determine the target evaluation standard of the corresponding water inflow sub-sequence. This embodiment considers the variation of water inflow in the historical data, divides the historical data based on the water inflow, and determines the appropriate target evaluation standard in each water inflow range through the threshold testing method, thereby improving the accuracy of the river and lake health evaluation standard in each water inflow range and the reliability of the river and lake health evaluation.

[0084] In some embodiments, in step S105, the step of constructing the threshold sequence corresponding to the index sub-sequence and testing each element in the threshold sequence to determine the target evaluation standard of the corresponding water inflow sub-sequence can include but is not limited to the following steps:

[0085] Step S401: constructing the threshold sequence according to a preset step size, with zero as the lower limit and the maximum index value in the index sub-sequence as the upper limit;

[0086] Step S402: selecting an element in the threshold sequence as a to-be-tested standard;

[0087] Step S403: screening out an to-be-tested sequence from the index sub-sequence, which is greater than the to-be-tested standard;

[0088] Step S404: testing the data distribution of the to-be-tested sequence, when the to-be-tested sequence passes the test, the to-be-tested standard is determined as the target evaluation standard of the corresponding water inflow sub-sequence; when the to-be-tested sequence fails the test, the next element in the threshold sequence is selected as the to-be-tested standard, and the steps of screening out the to-be-tested sequence from the index sub-sequence which is greater than the to-be-tested standard and testing the data distribution of the to-be-tested sequence are repeatedly executed.

[0089] In this embodiment, the maximum index value of the index sub-sequence X(t) is taken as the upper limit, denoted as X(t) Max 0 is taken as the lower limit, 0.1 is taken as the preset step size, and 0 to X(t) Max The threshold sequence TH[X(t)] is generated jIt can be understood that the preset step length can be set according to the accuracy requirement of the actual evaluation standard, and the embodiments of the application are not specifically limited.

[0090] From the first element (i.e. j = 1) of the threshold sequence, it is taken as a to-be-tested standard, and the index values greater than the to-be-tested standard in the index sub-sequence are screened out to obtain a to-be-tested sequence KS[X(t)] j The data distribution of the to-be-tested sequence is tested, if the to-be-tested sequence passes the test, the current to-be-tested standard is determined as the target evaluation standard of the corresponding inflow sub-sequence, and then the loop is ended; if the to-be-tested sequence does not pass the test, the next element in the threshold sequence is selected as the to-be-tested standard, and steps S403 to S404 are repeatedly executed.

[0091] In some embodiments, the step S404 of testing the data distribution of the to-be-tested sequence can include but is not limited to the following steps:

[0092] Step S501, the fitting degree of the to-be-tested sequence and the optimal distribution function is calculated by K-S test, and the sequence fitting degree is obtained;

[0093] Step S502, when the sequence fitting degree is greater than the expected fitting degree, it is determined that the to-be-tested sequence passes the test;

[0094] Step S503, when the sequence fitting degree is less than or equal to the expected fitting degree, it is determined that the to-be-tested sequence does not pass the test.

[0095] In this embodiment, the K-S test is the Kolmogorov-Smirnov test in Chinese, which is a statistical method for testing the fitting degree between sample data and reference distribution, and is widely used in hydrology, finance, biology and other fields. The fitting degree of the to-be-tested sequence and the optimal distribution function is calculated by K-S test, and the sequence fitting degree p[X(t)] j is obtained, which is as follows:

[0096] p[X(t)] j is a statistical parameter calculated by test, called asymptotic significance (two-tailed). The K-S test method judges the fitting degree of the to-be-tested sequence and the optimal distribution function according to the maximum vertical distance between two empirical distribution functions. In this example, the to-be-tested sequence is X(t), and the empirical distribution function of the to-be-tested sequence X(t) is:

[0097]

[0098] In the formula, F n [X(t)] is the empirical distribution function of the to-be-tested sequence X(t); is the indicator function of the sequence X(t); T is the sequence length, t = 1, 2, …, T.

[0099] The null hypothesis H0 of K-S test is F1[X(t)] = F2[X(t)], i.e., the empirical distribution of the sequence to be tested is consistent with the optimal distribution function; the alternative hypothesis H1 is F1[X(t)] ≠ F2[X(t)], i.e., the empirical distributions of the two sequences are inconsistent. To quantify the difference between the empirical distributions of the two sequences, define the maximum difference D, and the calculation formula is as follows:

[0100]

[0101] Wherein, sup represents the minimum upper bound of the set, and D T,α represents the rejection region of the sequence X(t) with capacity T at the confidence level α. When D ≥ D T,α , H0 is rejected; otherwise, H0 is accepted. To further quantify the significance of the difference between the two sequences, introduce p[X(t)] j , which is a specific value of the confidence level α. The value of the confidence level α is usually 95% or 99%, and the corresponding p[X(t)] j values are 0.05 and 0.01, respectively. If p[X(t)] j <0.01, it indicates that the determination result is strong, and H0 should be rejected, i.e., the two sequences follow different distributions and are not consistent; if 0.01 < p[X(t)] j <0.05, it indicates that the determination result is weak, and in this case, p[X(t)] j is considered to have a certain marginality, and H0 is usually rejected; if p[X(t)] j >0.05, H0 can be accepted.

[0102] If the fitting degree p[X(t)] j >0.05, it is considered that the empirical distribution of the sequence to be tested is consistent with the optimal distribution function, and the KS[X(t)] j is tested by testing the corresponding jth candidate evaluation standard in the threshold sequence as the target evaluation standard of evaluating the demand.

[0103] In some embodiments, the optimal distribution function of the index sub-sequence in step S501 can be determined by the following steps:

[0104] Step S601, obtaining a plurality of candidate distribution functions;

[0105] Step S602, calculating the information entropy and the partial entropy between the index sub-sequence and the candidate distribution function, and calculating the correlation coefficient between the index sub-sequence and the candidate distribution function according to the information entropy and the partial entropy;

[0106] Step S603, selecting the candidate distribution function with the largest correlation coefficient with the index sub-sequence as the optimal distribution function of the index sub-sequence.

[0107] In this embodiment, the correlation coefficient α[X(t)] i is used to measure the fitting degree of each index sub-sequence X(t) and the distribution curve F[·] i , and determine the optimal distribution function F[X(t)] Best . Wherein, i = 1, 2, …, 7 is the distribution curve number, in turn, normal distribution, lognormal distribution, exponential distribution, Weibull distribution, gamma distribution, binomial distribution and Poisson distribution. The correlation coefficient α[X(t)] i is a statistical parameter in information entropy theory, and the calculation steps are as follows:

[0108] First, the information entropy of X(t) and F[X(t)] i is calculated.

[0109]

[0110] Secondly, X(t) is the tth index value of the index sub-sequence; H X(t) is the information entropy of X(t); F[X(t)] i is the function value of the ith distribution function at the tth index value of the index sub-sequence; is the information entropy of F[X(t)] i .

[0111] Secondly, the partial entropy of X(t) and F[X(t)] i is calculated.

[0112]

[0113] Wherein, H X(t) {F[X(t)] i} is the partial entropy of X(t) about the ith distribution function; is the partial entropy of the ith distribution function about the tth index value of the index sub-sequence.

[0114] Then, the correlation coefficient of X(t) and F[X(t)] i is calculated.

[0115]

[0116] Finally, the optimal distribution function of X(t) is determined. Take the maximum α[X(t)] i as the goal, and select the corresponding F[X(t)] i as the optimal distribution function F[X(t)] Best of X(t).

[0117] Please refer to Figure 2Another aspect of this application proposes a method for assessing the health of rivers and lakes, which may include, but is not limited to, the following steps:

[0118] Step S701: Obtain target evaluation data for the target river and lake, wherein the target evaluation data includes target water inflow and target index values;

[0119] Step S702: Obtain the water volume range of each water quantum sequence, determine the corresponding water quantum sequence according to the water volume range to which the target water volume belongs, and obtain the corresponding target evaluation standard according to the water quantum sequence; wherein, the target evaluation standard is determined by the river and lake health evaluation standard determination method of the above embodiment.

[0120] Step S703: Analyze the target indicator values ​​according to the target evaluation criteria to obtain the river and lake health evaluation results.

[0121] In this embodiment, after obtaining the target evaluation standard corresponding to each inflow quantum sequence (inflow range) according to the river and lake health evaluation standard determination method of the above embodiment, it can be applied to the actual river and lake health evaluation. For example, the inflow value of the target river and lake in 2024 is obtained as 80 and the oxygen content index value is 0.5 (i.e., target evaluation data). Assuming that the oxygen content evaluation standard for the inflow range of 90-100 is determined to be 0.4 by the above river and lake health evaluation standard determination method, the inflow value of 80 belongs to the inflow range of 90-100. The oxygen content evaluation standard of 0.4 is selected. The oxygen content index value of 0.5 is greater than the oxygen content evaluation standard of 0.7. Therefore, a suitable evaluation result for the oxygen content of the river and lake can be obtained.

[0122] For example, taking river A as an example, the drainage area is 5813 km2, the river length is 163 km, and the average river gradient is 1.29‰. Taking the time series of the average annual water inflow of river A from 1961 to 2022, Q(t) (t=1,2,…,62), as an example, the specific implementation process of the method in the embodiment of this application is explained.

[0123] S1, Design Frequency Calculation:

[0124] The design frequency of river flow in year A was determined using P-III type hydrological frequency analysis software with goodness-of-fit calculation. The theoretical frequency curve was then obtained through fitting, as shown in the figure below. Figure 3 As shown.

[0125] S2, Evaluation Index Sample Screening:

[0126] Depend on Figure 3It can be seen that, based on the annual water volume Q(t), the sample of index values ​​QB(t) for evaluating the degree of variation in the flow process is divided into 4 groups, resulting in subsequences QB(t)-1, QB(t)-2, QB(t)-3, and QB(t)-4. The water volume ranges corresponding to the resulting water volume quantum sequences after Q(t) division are shown in Table 1. Table 1: Water Volume Ranges

[0127] Serial number 1 2 3 4 Annual water volume (billion m3) 67 ≤ Q(t) 54 ≤ Q(t) < 67 43.5 ≤ Q(t) < 54 36.2 ≤ Q(t) < 43.5

[0128] S3, preferred distribution function:

[0129] Calculate the QB(t) and distribution curve F[·] for each group. i The correlation coefficient α[X(t)] i See Table 2. Since QB(t) is a continuous sample, its correlation coefficient with the discrete distribution functions binomial and Poisson is not calculated.

[0130] Table 2. Results of Correlation Coefficient Calculation

[0131] Correlation coefficient QB(t)-1 QB(t)-2 QB(t)-3 QB(t)-4 Normal distribution 0.968 0.987 0.961 0.953 Lognormal distribution 0.986 0.974 0.984 0.966 Exponential distribution 0.952 0.977 0.982 0.991 Weibull distribution 0.946 0.965 0.976 0.984 Gamma distribution 0.955 0.943 0.968 0.978

[0132] As shown in Table 2, the optimal distribution function of QB(t)-1 is log-normal, the optimal distribution function of QB(t)-2 is normal, the optimal distribution function of QB(t)-3 is log-normal, and the optimal distribution function of QB(t)-4 is exponential.

[0133] S4, Evaluation criteria determined:

[0134] The KS test is used to traverse the threshold sequence TH[X(t)] of QB(t)-1, QB(t)-2, QB(t)-3, and QB(t)-4. j Determine the evaluation criteria. The threshold sequences for each group are as follows:

[0135] TH[X(t)]1={0,0.1,0.2,…,75.6};

[0136] TH[X(t)]2={0,0.1,0.2,…,73.5};

[0137] TH[X(t)]3={0,0.1,0.2,…,47.6};

[0138] TH[X(t)]3={0,0.1,0.2,…,38.1}.

[0139] After screening, the evaluation criteria for QB(t)-1, QB(t)-2, QB(t)-3 and QB(t)-4 are 54.3, 42.8, 35.4 and 10.6 respectively.

[0140] The incoming water quantity Q(t) of the river A in 2022 is 69.47 billion m3, and the index value QB(t) is 62.4. According to the Q(t) screening corresponding to the incoming water quantity range of QB(t)-1, since QB(t) = 62.4 > 54.3, the variation degree of the flow process meets the full score of the natural law of the river.

[0141] In some embodiments, another aspect of the embodiments of the present application also proposes a river and lake health evaluation standard determination system, comprising:

[0142] The first module is configured to obtain an incoming water quantity time sequence of a target river and lake, wherein the incoming water quantity time sequence comprises incoming water quantities in multiple unit times;

[0143] The second module is configured to sort the incoming water quantities in the incoming water quantity time sequence in size to obtain an incoming water quantity sorting sequence;

[0144] The third module is configured to divide the incoming water quantity sorting sequence to determine multiple incoming water quantity sub-sequences;

[0145] The fourth module is configured to obtain an index value corresponding to a unit time to which each incoming water quantity in the incoming water quantity sub-sequence belongs, and form an index sub-sequence according to the index values;

[0146] The fifth module is configured to construct a corresponding threshold value sequence according to the index sub-sequence, and test each element in the threshold value sequence to determine a target evaluation standard of the corresponding incoming water quantity sub-sequence, wherein each element of the threshold value sequence represents a candidate evaluation standard.

[0147] It can be understood that the contents in the above-mentioned river and lake health evaluation standard determination method embodiments are applicable to the system embodiments, the system embodiments specifically realize the same functions as the above-mentioned river and lake health evaluation standard determination method embodiments, and achieve the same beneficial effects as the above-mentioned river and lake health evaluation standard determination method embodiments.

[0148] The embodiments of the present application also provide an electronic device, which comprises a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing the connection and communication between the processor and the memory. The program is executed by the processor to realize the above-mentioned river and lake health evaluation standard determination method or river and lake health evaluation method. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0149] Please refer to Figure 4 , Figure 4 The hardware structure of the electronic device of another embodiment is illustrated, which comprises:

[0150] The processor 401 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, and is configured to execute related programs to implement the technical solutions provided by the embodiments of the present application.

[0151] The memory 402 can be implemented by a ROM (ReadOnly Memory), a static storage device, a dynamic storage device, or a RAM (Random Access Memory), and the like. The memory 402 can store an operating system and other application programs. When the technical solutions provided by the embodiments of the present application are implemented by software or firmware, the related program codes are stored in the memory 402 and are called and executed by the processor 401 to implement the river and lake health evaluation standard determination method or the river and lake health evaluation method.

[0152] The input / output interface 403 is configured to implement information input and output.

[0153] The communication interface 404 is configured to implement the communication interaction between the device and other devices. The communication can be implemented by a wired manner (for example, a USB, a network cable, or the like) or a wireless manner (for example, a mobile network, a WI-FI, a Bluetooth, or the like).

[0154] The bus 405 is configured to transmit information between the components (for example, the processor 401, the memory 402, the input / output interface 403, and the communication interface 404) of the device.

[0155] The processor 401, the memory 402, the input / output interface 403, and the communication interface 404 are connected to each other by the bus 405 to realize the communication connection between the components in the device.

[0156] The embodiments of the present application further provide a storage medium, which is a computer readable storage medium, and is configured to store computer readable information. The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the above-mentioned river and lake health evaluation standard determination method or the river and lake health evaluation method.

[0157] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include a high-speed random access memory and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory disposed remotely from the processor, which can be connected to the processor through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0158] The embodiments described in the embodiments of the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0159] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and can include more or fewer steps than shown in the figures, or combine certain steps, or different steps.

[0160] The system embodiments described above are only schematic, and the units described as separate components can or can not be physically separate, that is, can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0161] Those skilled in the art can understand that all or some of the steps in the above disclosed method, the functional modules / units in the system and the device can be implemented as software, firmware, hardware and appropriate combinations thereof.

[0162] The terms "first", "second", "third", "fourth" and the like used in the specification of the present application and the above-described drawings, if any, are used to distinguish similar objects, and do not necessarily have to describe a particular order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0163] It should be understood that, in the application, "at least one" refers to one or more, and "multiple" refers to two or more. "And / or" is used to describe the association relationship of the associated objects, which means that there can be three relationships, for example, "A and / or B" can represent three cases of only A, only B and A and B existing at the same time, wherein A and B can be singular or plural. The character " / " generally represents an "or" relationship between the front and rear associated objects. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can represent a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b and c can be single or multiple.

[0164] In several embodiments provided in the application, it should be understood that the disclosed system and method can be implemented in other ways. For example, the system embodiments described above are only illustrative, for example, the division of the above units is only a logical function division, and actual implementation can have another division mode, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be through some interface, indirect coupling or communication connection between systems or units, which can be electrical, mechanical or other forms.

[0165] The units described above as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0166] In addition, each functional unit in each embodiment of the application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0167] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0168] The preferred embodiments of the embodiments of the present application are described above with reference to the accompanying drawings, and are not limited to the scope of the embodiments of the present application. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the embodiments of the present application.

Claims

1. A method for determining river and lake health evaluation standards, characterized in that, Includes the following steps: Obtain the time series of water inflow for the target river or lake, wherein the water inflow time series includes water inflow within multiple unit time periods; The water inflow volume in the water inflow time series is sorted by size to obtain a water inflow sorting sequence; The water inflow sorting sequence is divided to determine multiple water inflow quantum sequences; Obtain the index value corresponding to each unit time of each water volume in the water quantum sequence, and form an index subsequence based on each index value; A corresponding threshold sequence is constructed based on the index subsequence, and each element in the threshold sequence is tested to determine the target evaluation standard for the corresponding water quantum sequence, wherein each element of the threshold sequence represents a candidate evaluation standard. The step of constructing a corresponding threshold sequence based on the index subsequence and examining each element in the threshold sequence to determine the target evaluation standard for the corresponding water quantum sequence includes the following steps: A threshold sequence is constructed with zero as the lower limit and the maximum index value in the index subsequence as the upper limit, according to a preset step size. Select one element from the threshold sequence as the criterion to be tested; The index values ​​greater than the test standard are selected from the subsequence of the indexes to obtain the test sequence; The data distribution of the sequence to be tested is tested. If the sequence to be tested passes the test, the test standard is determined as the target evaluation standard for the corresponding water quantum sequence. If the sequence to be tested fails the test, the next element in the threshold sequence is selected as the test standard, and the steps of filtering out the index values ​​greater than the test standard in the index subsequence to obtain the sequence to be tested and testing the data distribution of the sequence to be tested are repeated.

2. The method for determining river and lake health evaluation standards according to claim 1, characterized in that, The process of dividing the water inflow sorting sequence to determine multiple water inflow quantum sequences includes the following steps: The design frequency of the water inflow is calculated based on the number corresponding to each water inflow in the water inflow sorting sequence. The water inflow sequence is divided according to the preset division range of the design frequency to obtain multiple water inflow quantum sequences.

3. The method for determining river and lake health evaluation standards according to claim 2, characterized in that, The process of dividing the water inflow sorting sequence according to the design frequency range to obtain multiple water inflow quantum sequences includes the following steps: The theoretical frequency curve is obtained by performing curve fitting on each water inflow sequence and the corresponding design frequency. The water inflow of the theoretical frequency curve is divided according to the preset division range of the design frequency to obtain multiple water inflow quantum sequences.

4. The method for determining river and lake health evaluation standards according to claim 1, characterized in that, The process of examining the data distribution of the sequence to be examined includes the following steps: The KS test is used to calculate the goodness of fit between the sequence to be tested and the optimal distribution function, and the goodness of fit of the sequence is obtained. If the sequence fit is greater than the expected fit, then the sequence to be tested is determined to have passed the test. If the sequence fit is less than or equal to the expected fit, then the sequence to be tested is determined to have failed the test.

5. The method for determining river and lake health evaluation standards according to claim 4, characterized in that, The optimal distribution function of the index subsequence is determined through the following steps: Obtain multiple candidate distribution functions; Calculate the information entropy and partial entropy between the index subsequence and the candidate distribution function, and calculate the correlation coefficient between the index subsequence and the candidate distribution function based on the information entropy and the partial entropy; The candidate distribution function with the largest correlation coefficient with the index subsequence is selected as the optimal distribution function for the index subsequence.

6. A method for evaluating the health of rivers and lakes, characterized in that, Includes the following steps: Obtain target evaluation data for the target river and lake, wherein the target evaluation data includes target water inflow and target indicator values; The inflow volume range of each inflow quantum sequence is obtained, and the corresponding inflow quantum sequence is determined according to the inflow volume range to which the target inflow volume belongs. The corresponding target evaluation standard is obtained according to the inflow quantum sequence; wherein, the target evaluation standard is determined by the method for determining river and lake health evaluation standards as described in claim 1. The target indicator values ​​are analyzed according to the target evaluation criteria to obtain the river and lake health evaluation results.

7. A system for determining standards for evaluating the health of rivers and lakes, characterized in that, include: The first module is used to obtain the water inflow time series of the target river and lake, wherein the water inflow time series includes water inflow within multiple unit time periods; The second module is used to sort the water inflow in the water inflow time series by size to obtain a water inflow sorting sequence. The third module is used to divide the water inflow sorting sequence and determine multiple water inflow quantum sequences; The fourth module is used to obtain the index value corresponding to each unit time of each water volume in the water quantum sequence, and to form an index subsequence based on each index value; The fifth module is used to construct a corresponding threshold sequence based on the index subsequence, and to examine each element in the threshold sequence to determine the target evaluation standard for the corresponding water quantum sequence, wherein each element of the threshold sequence represents a candidate evaluation standard. The fifth module is specifically used to perform the following steps: A threshold sequence is constructed with zero as the lower limit and the maximum index value in the index subsequence as the upper limit, according to a preset step size. Select one element from the threshold sequence as the criterion to be tested; The index values ​​greater than the test standard are selected from the subsequence of the indexes to obtain the test sequence; The data distribution of the sequence to be tested is tested. If the sequence to be tested passes the test, the test standard is determined as the target evaluation standard for the corresponding water quantum sequence. If the sequence to be tested fails the test, the next element in the threshold sequence is selected as the test standard, and the steps of filtering out the index values ​​greater than the test standard in the index subsequence to obtain the sequence to be tested and testing the data distribution of the sequence to be tested are repeated.

8. An electronic device, characterized in that, The electronic device includes a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for enabling communication between the processor and the memory, wherein the program, when executed by the processor, implements the steps of the method as described in any one of claims 1 to 6.

9. A storage medium, said storage medium being a computer-readable storage medium for computer-readable storage, characterized in that, The storage medium stores one or more programs, which can be executed by one or more processors to implement the steps of the method according to any one of claims 1 to 6.

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