River and lake health evaluation method, system, equipment and medium

Abstract

The invention discloses a river and lake health evaluation method, system and device and a medium, and the method comprises the steps: obtaining the health index data of a river and a lake and a multi-year average daily flow sequence set; intra-year period division is carried out on the multi-year average daily flow sequence set to obtain a plurality of intra-year period data, and experience distributions of the intra-year period data with adjacent time are different; performing grade evaluation table generation processing on all the intra-year period data to obtain a period evaluation table corresponding to each intra-year period data; and according to the health index data, performing health mapping evaluation on all the period evaluation tables to obtain a health evaluation result of the river and lake. The method can effectively improve objectivity and accuracy of river and lake health evaluation. The invention relates to the technical field of hydrology science.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrological science and technology, and in particular to a method, system, device and medium for evaluating the health of rivers and lakes. Background Art

[0002] The evaluation of the health of rivers and lakes refers to a comprehensive and systematic assessment of the health status of rivers or lakes to understand their ecological, environmental and functional states, and to provide a scientific basis for their protection and management. It is of great significance for improving the level of river and lake treatment and protection and promoting the construction of water ecological civilization.

[0003] At present, the existing river and lake health evaluation technologies mainly achieve the health evaluation of rivers and lakes through biological index evaluation methods, physical and chemical index evaluation methods or comprehensive evaluation methods. However, since these methods rely heavily on expert experience and do not consider the distribution characteristics of the indexes to be evaluated, the objectivity and accuracy of the river and lake health evaluation results are not satisfactory.

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

[0005] An object of the present invention is to solve at least to some extent one of the technical problems existing in the related art.

[0006] To this end, an object of an embodiment of the present invention is to provide a method, system, device and medium for evaluating the health of rivers and lakes, wherein the method can effectively improve the objectivity and accuracy of the river and lake health evaluation.

[0007] To achieve the above technical object, the technical solutions adopted in the embodiments of the present application include:

[0008] In a first aspect, an embodiment of the present application provides a method for evaluating the health of rivers and lakes, including:

[0009] Obtaining health index data of rivers and lakes and a set of multi-year average daily flow sequences;

[0010] Dividing the set of multi-year average daily flow sequences into annual cycle data, and the empirical distributions of the adjacent annual cycle data in time are different;

[0011] Performing generation processing of a grade evaluation table on all the annual cycle data to obtain a cycle evaluation table corresponding to each annual cycle data;

[0012] According to the health index data, performing a health mapping evaluation on all the cycle evaluation tables to obtain the health evaluation result of the rivers and lakes.

[0013] In addition, according to the method of the above embodiment of the present application, the following additional technical features may also be provided:

[0014] Further, in an embodiment of the present application, the step of performing intra-year cycle division on the multi-year average daily flow sequence set to obtain a plurality of intra-year cycle data includes:

[0015] Obtain a division threshold;

[0016] Obtain a division start point, a division check point, and a division end point;

[0017] Perform intra-year cycle division on the multi-year average daily flow sequence set according to the division threshold, the division start point, the division check point, and the division end point to obtain a plurality of the intra-year cycle data.

[0018] Further, in an embodiment of the present application, the step of performing intra-year cycle division on the multi-year average daily flow sequence set according to the division threshold, the division start point, the division check point, and the division end point to obtain a plurality of the intra-year cycle data includes:

[0019] Perform a first sequence division on the multi-year average daily flow sequence set according to the division start point and the division check point to obtain a first flow sequence;

[0020] Perform a second sequence division on the multi-year average daily flow sequence set according to the division check point and the division end point to obtain a second flow sequence;

[0021] Verify the empirical distribution consistency of the second flow sequence according to the first flow sequence to obtain an empirical distribution verification result;

[0022] Perform a first threshold verification on the division end point according to the division threshold to obtain a first threshold verification result;

[0023] If the empirical distribution verification result shows different empirical distributions and the first threshold verification result shows that the division end point is less than the division threshold, then retain the first flow sequence, update the division start point according to the division check point, and update the division check point and the division end point according to the updated division start point, and then return to execute the step of obtaining the division start point, the division check point, and the division end point; or, if the empirical distribution verification result shows different empirical distributions and the first threshold verification result shows that the division end point is equal to the division threshold, then obtain a plurality of intra-year cycle data according to the current second flow sequence and all the first flow sequences.

[0024] Further, in an embodiment of the present application, the method further includes:

[0025] If the empirical distribution verification result shows that the empirical distributions are the same and the first threshold verification result shows that the division termination point is less than the division threshold, then update the division termination point, and then return to execute the steps of obtaining the division starting point, division verification point, and division termination point;

[0026] Or,

[0027] If the empirical distribution verification result shows that the empirical distributions are the same and the first threshold verification result shows that the division termination point is equal to the division threshold, then perform a second threshold verification on the division verification point according to the division threshold to obtain a second threshold verification result.

[0028] Further, in an embodiment of the present application, the method further includes:

[0029] If the second threshold verification result shows that the division verification point is less than the division threshold, then update the division verification point, and update the division termination point according to the updated division verification point, and then return to execute the steps of obtaining the division starting point, division verification point, and division termination point;

[0030] Or,

[0031] If the second threshold verification result shows that the division verification point is equal to the division threshold, then obtain a third traffic sequence according to the current first traffic sequence and the current second traffic sequence, and obtain several annual cycle data according to the third traffic sequence and all previous first traffic sequences.

[0032] Further, in an embodiment of the present application, the expression form of the empirical distribution function of the first traffic sequence is:

[0033]

[0034] Wherein, is the empirical distribution function; is the first traffic sequence; i is the division starting point; j is the division verification point; t is the time point of the first traffic sequence in the time series; is the indicator function of the first traffic sequence.

[0035] Further, in an embodiment of the present application, perform a level evaluation table generation process on the annual cycle data to obtain a cycle evaluation table, including:

[0036] Obtain several annual cycle index sub-data of the annual cycle data, and each of the annual cycle index sub-data corresponds to a different type of river and lake health evaluation index;

[0037] Perform data analysis on all the sub-data of the annual cycle indicators to obtain the indicator mean and indicator standard deviation of each sub-data of the annual cycle indicator;

[0038] Obtain the cycle evaluation table according to all the indicator means and all the indicator standard deviations.

[0039] Further, in an embodiment of the present application, the health mapping evaluation is performed on all the cycle evaluation tables according to the health indicator data to obtain the health evaluation result of the river and lake, including:

[0040] Perform table screening on all the cycle evaluation tables according to the health indicator data to obtain the target evaluation table corresponding to the health indicator data;

[0041] Perform index scoring evaluation on the health indicator data according to the target evaluation table to obtain the health evaluation result of the river and lake.

[0042] In a second aspect, an embodiment of the present application provides a river and lake health evaluation system, including:

[0043] A first processing unit, configured to obtain the health indicator data of the river and lake and the multi-year average daily flow sequence set;

[0044] A second processing unit, configured to perform annual cycle division on the multi-year average daily flow sequence set to obtain a plurality of annual cycle data, and the empirical distributions of the adjacent annual cycle data in time are different;

[0045] A third processing unit, configured to perform grade evaluation table generation processing on all the annual cycle data to obtain a cycle evaluation table corresponding to each annual cycle data;

[0046] A fourth processing unit, configured to perform health mapping evaluation on all the cycle evaluation tables according to the health indicator data to obtain the health evaluation result of the river and lake.

[0047] In a third aspect, an embodiment of the present application further provides an electronic device, including:

[0048] At least one processor;

[0049] At least one memory, configured to store at least one program;

[0050] 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 above.

[0051] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, in which a program executable by a processor is stored, and the program executable by the processor is used to implement the method of the first aspect above when executed by the processor.

[0052] Advantages and beneficial effects of the present application will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present application:

[0053] A method, system, device and medium for evaluating the health of rivers and lakes disclosed in an embodiment of the present application, wherein the method obtains health index data of rivers and lakes and a set of multi-year average daily flow sequences; divides the set of multi-year average daily flow sequences into annual cycles to obtain several annual cycle data, and the empirical distributions of adjacent annual cycle data in time are different; performs a generation process of a rating evaluation form on all the annual cycle data to obtain a cycle evaluation form corresponding to each annual cycle data; and performs a health mapping evaluation on all the cycle evaluation forms according to the health index data to obtain a health evaluation result of the river or lake. By dividing the set of multi-year average daily flow sequences into annual cycles to obtain several annual cycle data, and the empirical distribution of each annual cycle data is different from that of other adjacent annual cycle data in the time series, and then performing a health evaluation on the cycle evaluation forms generated from the annual cycle data based on the health index data, the method can effectively improve the objectivity and accuracy of the health evaluation of rivers and lakes. Description of the Drawings

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following introduces the accompanying drawings of the related technical solutions in the embodiments of the present application or the prior art. It should be understood that the accompanying drawings in the following introduction are only for conveniently and clearly expressing some embodiments of the technical solutions in the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative efforts.

[0055] Figure 1 It is a schematic flowchart of a method for evaluating the health of rivers and lakes provided by an embodiment of the present application;

[0056] Figure 2 It is a schematic structural diagram of a system for evaluating the health of rivers and lakes provided by an embodiment of the present application;

[0057] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Detailed Embodiments

[0058] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present application, and should not be construed as a limitation to the present application. For the step numbers in the following embodiments, they are only set for the convenience of explanation and illustration, and no limitation is imposed on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field 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.

[0060] Currently, the existing river and lake health assessment technologies mainly achieve the health assessment of rivers and lakes through biological index assessment methods, physical and chemical index assessment methods, or comprehensive assessment methods. Among them, the biological index assessment method uses aquatic organisms as indicator species, and reflects the health status of rivers and lakes by monitoring changes in the species, quantity, distribution, etc. of aquatic organisms. Specifically, the Fish Index of Biotic Integrity (F-IBI), Benthic Index of Biotic Integrity (B-IBI), Shannon-Wienner diversity index, plankton assessment method, and biological integrity index can be used to reflect the health status of rivers and lakes.

[0061] The physical and chemical index assessment method reflects the health status of rivers and lakes by water quality, hydrological characteristics, river morphology, or lake geomorphology. Among them, the representative indicators of water quality assessment include chemical oxygen demand (COD), biochemical oxygen demand (BOD), ammonia nitrogen, total phosphorus, dissolved oxygen, etc.; the hydrological characteristics assessment starts from flow, water level, and flow velocity, and its representative indicator is IHA (Indicators of Hydrologic Alteration). The assessment of river morphology or lake geomorphology includes indicators such as the meandering degree of the river channel, river width, and water depth.

[0062] The comprehensive assessment method constructs a comprehensive assessment system by selecting multiple indicators reflecting the health of rivers and lakes and following the path of weight assignment - score assignment to analyze the health status of rivers and lakes. For example, the Pressure - State - Response model (PSR) is used to analyze the mutual relationship between pressure, state, and response to achieve the assessment of the health status of rivers and lakes; or, for another example, the weight between the hierarchical structures of the judgment matrix is determined, and the health assessment result of the river and lake is obtained by quantifying the comprehensive assessment indicators.

[0063] However, since the biological index evaluation method and the physical and chemical index evaluation method basically use the quantile method to divide the evaluation levels of evaluation indicators, the commonly used quantiles include 10%, 25%, 50%, 75%, 80%, 90%, etc. The setting of quantiles depends on expert experience and cannot reflect the distribution law of the evaluation indicators themselves. As a result, the biological index evaluation method and the physical and chemical index evaluation method cannot consider the distribution characteristics of the indicators to be evaluated, and the objectivity and accuracy of the river and lake health evaluation results are not satisfactory. Moreover, the comprehensive evaluation method generally uses the expert experience method and the subjective-objective combination method (objective weighting method + expert experience method) to determine the weights. Both the evaluation index system and the recursive hierarchical structure strongly depend on expert experience, making the river and lake health evaluation results lack objectivity and the accuracy of the river and lake health evaluation is also not satisfactory.

[0064] In addition, the above methods usually set the lower standard in the dry season of the river and lake as the annual average standard, which does not consider the differences in natural geographical conditions, climate characteristics, economic and social development and other factors of different rivers and lakes. The constraint strength of the river and lake health evaluation is small, and thus the reference value of the river and lake health evaluation results is not high.

[0065] In view of this, the embodiments of the present invention provide a river and lake health evaluation method, system, device and medium. Among them, the method divides the annual average daily flow sequence set into annual cycle data, and each annual cycle data has a different empirical distribution from other annual cycle data adjacent to it in the time series. Then, based on the cycle evaluation table generated from the annual cycle data, it is possible to adaptively generate a higher degree of adaptation evaluation level for each annual cycle of the river and lake while fully considering the distribution characteristics of the indicators to be evaluated, without relying on expert experience to determine the evaluation level or weight, which is beneficial to improving the objectivity and accuracy of the river and lake health evaluation results.

[0066] In addition, the method constructs a cycle evaluation table through several annual cycle index sub-data, which can fully consider the differences in natural geographical conditions, climate characteristics, economic and social development and other factors of the river and lake, is beneficial to improving the constraint strength of the river and lake health evaluation, and thus improves the reference value of the river and lake health evaluation results.

[0067] Refer to Figure 1 , in the embodiments of the present application, a river and lake health evaluation method includes:

[0068] Step 110, obtaining the health index data of the river and lake and the annual average daily flow sequence set;

[0069] In the embodiments of the present application, the health index data may be the index data of a river or lake on a certain date, and the index data may include at least one of the longitudinal connectivity index of the river or lake, the satisfaction degree of ecological flow, the status of the aquatic plant community, the public satisfaction degree, etc.; the set of annual average daily flow sequences includes several annual average daily flow data of the river or lake, and the corresponding annual time dates of each annual average daily flow data are different. The number of annual average daily flow data in the set of annual average daily flow sequences can be flexibly set according to the actual situation, and the embodiments of the present application will not elaborate on this here.

[0070] Step 120: Perform annual cycle division on the set of annual average daily flow sequences to obtain several annual cycle data, and the empirical distributions of adjacent annual cycle data in time are different;

[0071] In the embodiments of the present application, based on the time date sequence within a year, the set of annual average daily flow sequences of the river or lake can be divided into annual cycles to obtain several annual cycle data. The number of the annual cycle data can be an integer greater than or equal to 1. Moreover, among all the obtained annual cycle data, two adjacent annual cycle data in the time sequence follow different empirical distributions, that is, there is no consistency between two adjacent annual cycle data in the time sequence.

[0072] In some embodiments, step 120: Perform annual cycle division on the set of annual average daily flow sequences to obtain several annual cycle data, including:

[0073] A1: Obtain the division threshold;

[0074] A2: Obtain the division starting point, division test point, and division ending point;

[0075] In the embodiments of the present application, the set of annual average daily flow sequences can be divided into annual cycles in a cyclic manner, so as to divide each annual average daily flow data in the set of annual average daily flow sequences into the corresponding annual cycle, thereby obtaining several annual cycle data.

[0076] It can be understood that the division threshold can be set according to the actual situation. Specifically, if the set of annual average daily flow sequences is a sequence set of annual average daily flow data in a common year, the corresponding division threshold can be 365; or, if the set of annual average daily flow sequences contains a sequence set of annual average daily flow data in a leap year, that is, when the set of annual average daily flow sequences contains the annual average daily flow data with the time date of February 29th, the corresponding division threshold can be 366.

[0077] It should be noted that the division starting point is used to indicate the starting point for dividing the annual average daily flow data in the annual average daily flow sequence set during the current loop process; the division check point and the division end point are similar to the aforementioned division starting point and can be simply deduced by analogy.

[0078] It is worth mentioning that the division starting point, the division check point, and the division end point in the embodiments of the present application can be points on the time series, and the points on the time series can be associated with the annual average daily flow data corresponding to the time and date in the annual average daily flow sequence set. For example, if January 1st is the first day of the year, the annual average daily flow data on January 1st can correspond to the first point on the time series; or, if January 3rd is the third day of the year, the annual average daily flow data on January 1st can correspond to the third point on the time series.

[0079] In addition, the division check point in the embodiments of the present application can be greater than or equal to the division starting point, and the division end point can be greater than or equal to the division check point. Exemplarily, if the current loop process is the first loop process, the division starting point, the division check point, and the division end point can be preset values. For example, both the division starting point and the division check point are 1, and the division end point is 2; or, if the current loop process is the second or more loop processes, the division starting point is the division starting point at the end of the previous loop process, and the division check point and the division end point are the same.

[0080] A3. Perform annual cycle division on the annual average daily flow sequence set according to the division threshold, the division starting point, the division check point, and the division end point to obtain a plurality of the annual cycle data.

[0081] Further, the step A3 of performing annual cycle division on the annual average daily flow sequence set according to the division threshold, the division starting point, the division check point, and the division end point to obtain a plurality of the annual cycle data includes:

[0082] A31. Perform a first sequence division on the annual average daily flow sequence set according to the division starting point and the division check point to obtain a first flow sequence;

[0083] A32. Perform a second sequence division on the annual average daily flow sequence set according to the division check point and the division end point to obtain a second flow sequence;

[0084] A33. Perform empirical distribution consistency verification on the second flow sequence according to the first flow sequence to obtain an empirical distribution verification result;

[0085] A34. Perform a first threshold verification on the division termination point according to the division threshold to obtain a first threshold verification result;

[0086] A35. If the empirical distribution verification result is that the empirical distributions are different and the first threshold verification result is that the division termination point is less than the division threshold, then retain the first flow sequence, update the division start point according to the division test point, and update the division test point and the division termination point according to the updated division start point, and then return to execute the steps of obtaining the division start point, the division test point, and the division termination point;

[0087] Or, A36. If the empirical distribution verification result is that the empirical distributions are different and the first threshold verification result is that the division termination point is equal to the division threshold, then obtain several annual cycle data according to the current second flow sequence and all the first flow sequences.

[0088] In the embodiments of the present application, for a certain cyclic process, the multi-year average daily flow sequence set can be sequence-divided according to the division start point and the division test point in the current cyclic process, so as to obtain several multi-year average daily flow data between the division start point and the division test point. Specifically, if the point value of the division start point is 2, the point value of the division test point is 4, and the multi-year average daily flow sequence set is {Q1, Q2, Q3, Q4, Q5}, then the corresponding first flow sequence includes the second multi-year average daily flow data Q2, the third multi-year average daily flow data Q3, and the fourth multi-year average daily flow data Q4 in the time series.

[0089] It can be understood that the content of the second flow sequence is similar to that of the foregoing first flow sequence and can be simply analogously derived. The empirical distribution consistency verification in step A33 can be to calculate the consistency between the first flow sequence and the second flow sequence based on the K-S (Kolmogorov-Smirnov) test method to obtain the empirical distribution verification result. Exemplarily, the empirical distribution function of the first flow sequence can be expressed as:

[0090]

[0091] Wherein, is the empirical distribution function; is the first flow sequence; i is the division start point; j is the division test point; t is the time point of the first flow sequence in the time series; is the indicator function of the first flow sequence.

[0092] It should be noted that the empirical distribution function of the second traffic sequence is similar to that of the aforementioned first traffic sequence and can be simply inferred by analogy. After obtaining the empirical distribution functions of the first traffic sequence and the second traffic sequence respectively, the confidence level between the two empirical distribution functions can be calculated, and the significance level between the first traffic sequence and the second traffic sequence can be calculated based on the obtained confidence level. If the significance level is less than the preset critical threshold, an empirical distribution verification result indicating different empirical distributions is generated; or, if the significance level is greater than or equal to the preset critical threshold, an empirical distribution verification result indicating the same empirical distribution is generated. Among them, the preset critical threshold can be any one of 0.01, 0.02, 0.05, etc. The examples in this application are only for illustration.

[0093] It is worth mentioning that the first threshold verification can be to compare the magnitude relationship between the division threshold and the division end point to obtain the first threshold verification result. Specifically, if the empirical distribution verification result is that the empirical distributions are different and the first threshold verification result is that the division end point is less than the division threshold, it means that there is no consistency between the first traffic sequence and the second traffic sequence and there are multi-year average daily traffic data in the multi-year average daily traffic sequence set that have not been cyclically traversed. At this time, the first traffic sequence in the current loop process can be retained, and then the point value of the division test point is assigned to the division start point to obtain the updated division start point. Then, based on the updated division start point, the division test point and the division end point are updated. Specifically, the updated division test point can be made equal to the updated division end point, and the updated division end point is equal to the sum of the updated division start point and the value 1. Finally, return to execute step A2.

[0094] It should be added that if the empirical distribution verification result is that the empirical distributions are different and the first threshold verification result is that the division end point is equal to the division threshold, it means that there is no consistency between the first traffic sequence and the second traffic sequence and there are no multi-year average daily traffic data in the multi-year average daily traffic sequence set that have not been cyclically traversed. That is, the first traffic sequence and the second traffic sequence are the last two traffic sequences generated by the multi-year average daily traffic sequence set, and the first traffic sequence and the second traffic sequence are a sequence set of two adjacent multi-year average daily traffic data in the time series. At this time, each first traffic sequence retained in the previous loop process can be respectively determined as an intra-year cycle data, the first traffic sequence obtained in the current loop process can be determined as an intra-year cycle data, and the second traffic sequence obtained in the current loop process can be determined as an intra-year cycle data. Several multi-year average daily traffic data in each intra-year cycle data belong to the same empirical distribution.

[0095] In some embodiments, the method further includes:

[0096] A37. If the empirical distribution verification result shows that the empirical distributions are the same and the first threshold verification result shows that the division termination point is less than the division threshold, then update the division termination point, and then return to execute the steps of obtaining the division starting point, division checkpoint, and division termination point;

[0097] Or,

[0098] A38. If the empirical distribution verification result shows that the empirical distributions are the same and the first threshold verification result shows that the division termination point is equal to the division threshold, then perform a second threshold verification on the division checkpoint according to the division threshold to obtain a second threshold verification result.

[0099] In the embodiments of the present application, if the empirical distribution verification result shows that the empirical distributions are the same and the first threshold verification result shows that the division termination point is less than the division threshold, it indicates that there is consistency between the first flow sequence and the second flow sequence and there are multi-year average daily flow data in the multi-year average daily flow sequence set that have not been cyclically traversed. At this time, the division termination point can be updated. Specifically, it can be to perform an operation of adding 1 to the point value of the division termination point to obtain the updated division termination point, and then return to execute step A2.

[0100] It can be understood that if the empirical distribution verification result shows that the empirical distributions are the same and the first threshold verification result shows that the division termination point is equal to the division threshold, then the size relationship between the division threshold and the division checkpoint in the current loop process can be compared to obtain the second threshold verification result.

[0101] In some embodiments, the method further includes:

[0102] A381. If the second threshold verification result shows that the division checkpoint is less than the division threshold, then update the division checkpoint, and update the division termination point according to the updated division checkpoint, and then return to execute the steps of obtaining the division starting point, division checkpoint, and division termination point;

[0103] Or,

[0104] A382. If the second threshold verification result shows that the division checkpoint is equal to the division threshold, then obtain a third flow sequence according to the current first flow sequence and the current second flow sequence, and obtain several intra-year cycle data according to the third flow sequence and all previous first flow sequences.

[0105] In an embodiment of the present application, if the second threshold verification result is that the division checkpoint is less than the division threshold, the point value of the division checkpoint can be incremented by 1 to obtain an updated division checkpoint. At the same time, the updated division checkpoint is incremented by 1 again, and the point value of the division checkpoint after the second increment is assigned to the division termination point, and then step A2 is executed again.

[0106] It can be understood that if the second threshold verification result is that the division checkpoint is equal to the division threshold, it means that the division checkpoint has reached the division termination point. The first flow sequence and the second flow sequence are the last two flow sequences of the multi-year average daily flow sequence set, and the first flow sequence and the second flow sequence are consistent, that is, the first flow sequence and the second flow sequence belong to the same annual cycle. At this time, the current first flow sequence and the second flow sequence can be integrated, and the obtained third flow sequence is determined as an annual cycle data. At the same time, each first flow sequence retained in the previous loop process is respectively determined as an annual cycle data.

[0107] It is worth mentioning that the annual cycle division in the embodiment of the present application can divide the multi-year average daily flow data into annual cycle data according to the time and date within the year, so as to obtain several annual cycle data. Each annual cycle data is a set of multi-year average daily flow data distinguished by time periods. These several annual cycle data can not only fully reflect the distribution characteristics of the evaluation indexes to be evaluated of the river and lake, but also be conducive to improving the adaptability of the subsequent generated evaluation level to the river and lake, and further conducive to improving the objectivity and accuracy of the health evaluation result of the river and lake.

[0108] Step 130: Perform processing to generate a grade evaluation table for all the annual cycle data to obtain a cycle evaluation table corresponding to each annual cycle data;

[0109] In an embodiment of the present application, a cycle average table corresponding to each annual cycle data can be generated based on each multi-year average daily flow data in the annual cycle data. The sum of the annual cycles of all the cycle average tables is the entire time series.

[0110] In some embodiments, performing processing to generate a grade evaluation table for the annual cycle data to obtain a cycle evaluation table includes:

[0111] B1: Obtain several annual cycle index sub-data of the annual cycle data, and each annual cycle index sub-data corresponds to a different type of river and lake health evaluation index;

[0112] B2: Perform data analysis on all the annual cycle index sub-data to obtain the index mean and index standard deviation of each annual cycle index sub-data;

[0113] B3. Obtain the cycle evaluation form according to all the mean values of the indicators and all the standard deviations of the indicators.

[0114] In the embodiment of the present application, for the cycle data of a certain year, first, the cycle within the year corresponding to all the multi-year average daily flow data of the cycle data within the year can be obtained. The cycle within the year can be constructed from the time dates of all the multi-year average daily flow data of the cycle data within the year. Then, based on the obtained cycle within the year, a number of sub-data of the cycle indicators within the year corresponding to the cycle data within the year are determined. Each sub-data of the cycle indicators within the year is used to characterize the river and lake health evaluation indicators during the corresponding cycle within the year, which can specifically be the longitudinal connectivity index of the river and lake, the satisfaction degree of ecological flow, the status of the aquatic plant community, or the public satisfaction degree during the corresponding cycle within the year.

[0115] It can be understood that for a certain sub-data of the cycle indicators within the year of the cycle data within the year, the mean value μ of the sub-data of the cycle indicators within the year can be calculated respectively n and the standard deviation σ n ; then, based on the three-sigma (3σ) principle, obtain the corresponding sub-evaluation form for the sub-data of the cycle indicators within the year. Specifically, it can be to count μ n -3σ n 、μ n -2σ n 、μ n -σ n 、μ n 、μ n +σ n 、μ n +2σ n and μ n +3σ n corresponding index thresholds, and record them as index thresholds and Then, based on all the obtained index thresholds, construct the sub-evaluation form corresponding to the sub-data of the cycle indicators within the year. The sub-evaluation form can be as shown in Table 1 below:

[0116] Table 1

[0117]

[0118] It should be noted that the sub-evaluation forms of the remaining sub-data of the cycle indicators within the year are similar to the foregoing content and can be simply analogized. After obtaining the sub-evaluation forms of all the sub-data of the cycle indicators within the year of the cycle data within the year, all the sub-evaluation forms can be integrated to obtain the cycle evaluation form corresponding to the cycle data within the year. The same applies to the remaining cycle data within the year, which will not be elaborated herein in the present application.

[0119] Step 140: Based on the health index data, perform a health mapping evaluation on all the cycle evaluation forms to obtain the health evaluation result of the river and lake.

[0120] In the embodiment of the present application, based on the health index data of the river and lake at a certain time and date and all the cycle evaluation forms, the health evaluation result of the river and lake at this time and date can be obtained by looking up the table and assigning scores.

[0121] In some embodiments, Step 140: Based on the health index data, perform a health mapping evaluation on all the cycle evaluation forms to obtain the health evaluation result of the river and lake, includes:

[0122] C1: Based on the health index data, perform form screening on all the cycle evaluation forms to obtain the target evaluation form corresponding to the health index data;

[0123] C2: Based on the target evaluation form, perform index score evaluation on the health index data to obtain the health evaluation result of the river and lake.

[0124] In the embodiment of the present application, based on the time and date attribute in the health index data and the annual cycle corresponding to each cycle evaluation form, by determining whether the time and date attribute in the health index data belongs within the annual cycle of the cycle evaluation form, the cycle evaluation form corresponding to the health index data is determined, and the cycle evaluation form corresponding to the health index data is determined as the target evaluation form.

[0125] It can be understood that in the embodiment of the present application, taking the health index data including the longitudinal connectivity index and the ecological flow satisfaction degree of the river and lake as an example, Step C2 can be to respectively obtain the grade scores of the longitudinal connectivity index of the river and lake on the corresponding sub-evaluation form and the grade scores of the ecological flow satisfaction degree on the corresponding sub-evaluation form, and perform an accumulation operation on all the obtained grade scores to obtain the health evaluation result of the river and lake.

[0126] Next, a river and lake health evaluation system proposed according to an embodiment of the present application will be described in detail with reference to the accompanying drawings.

[0127] Refer to Figure 2 , a river and lake health evaluation system proposed in the embodiment of the present application, includes:

[0128] The first processing unit 101 is used to obtain the health index data of the river and lake and the multi-year average daily flow sequence set;

[0129] The second processing unit 102 is used to perform annual cycle division on the multi-year average daily flow sequence set to obtain several annual cycle data, and the empirical distributions of the adjacent annual cycle data in time are different;

[0130] The third processing unit 103 is configured to perform a processing of generating a rating evaluation form for all the annual cycle data, so as to obtain a cycle evaluation form corresponding to each annual cycle data;

[0131] The fourth processing unit 104 is configured to perform a health mapping evaluation on all the cycle evaluation forms according to the health index data, so as to obtain a health evaluation result of the river and lake.

[0132] It can be understood that the content in the above method embodiments is applicable to the system embodiments of the present application. The functions specifically implemented by the system embodiments of the present application are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0133] Referring to Figure 3 , the embodiments of the present application further provide an electronic device, including:

[0134] At least one processor 201;

[0135] At least one memory 202, configured to store at least one program;

[0136] 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 embodiments.

[0137] Similarly, it can be understood that the content in the above method embodiments is applicable to the device embodiments of the present application. The functions specifically implemented by the device embodiments of the present application are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0138] The embodiments of the present application further provide a computer-readable storage medium, in which a program executable by a processor 201 is stored, and the program executable by the processor 201 is used to implement the above method embodiments when executed by the processor 201.

[0139] Similarly, the content in the above method embodiments is applicable to the computer-readable storage medium embodiments of the present application. The functions specifically implemented by the computer-readable storage medium embodiments of the present application are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0140] In some alternative embodiments, the functions / operations recited in the block diagrams may not occur in the order presented in the operational illustrations. For example, depending on the functions / operations involved, two blocks shown in succession may actually be executed substantially concurrently or the blocks may sometimes be executed in reverse order. Additionally, the embodiments presented and described in the flowcharts of the present application are provided by way of example for the purpose of providing a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logical flows presented herein. Alternative embodiments are contemplated in which the order of various operations is altered and in which sub-operations described as part of a larger operation are executed independently.

[0141] Moreover, although the present application has been described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and / or features may be integrated in a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It should also be understood that a detailed discussion of the actual implementation of each module is not necessary for an understanding of the present application. Rather, given the attributes, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the modules will be understood within the ordinary skill of an engineer. Thus, those of ordinary skill in the art can implement the present application as set forth in the claims without undue experimentation. It should also be understood that the specific concepts disclosed are illustrative only and are not intended to limit the scope of the present application, which is determined by the full scope of the appended claims and their equivalents.

[0142] If a function is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application, in essence or the part that contributes to the prior art or part of the technical solution, may be embodied in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method according to the embodiments of the present application. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0143] The logic and / or steps represented in the flowchart or otherwise described herein can, for example, be considered a definitional sequence of executable instructions for implementing logical functions and can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. As used in this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with the instruction execution system, apparatus, or device.

[0144] More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection (electronic device) having one or more wirings, a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which a program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other suitable processing as necessary, and then stored in a computer memory.

[0145] It should be understood that the various parts of this application can be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0146] In the foregoing description of this specification, the descriptions with reference to the terms "one embodiment / example", "another embodiment / example", or "certain embodiments / examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of this application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0147] Although embodiments of the present application have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present application. The scope of the present application is defined by the claims and their equivalents.

[0148] The above is a specific description of the preferred embodiments of the present application, but the present application is not limited to the embodiments. Those skilled in the art can make various equivalent deformations or substitutions without departing from the spirit of the present application, and these equivalent deformations or substitutions are all included within the scope defined by the claims of the present application.

Claims

1. A method for evaluating the health of rivers and lakes, characterized in that: include: Obtain river and lake health indicator data and multi-year average daily flow series; The multi-year average daily flow series set is divided into annual periods to obtain a number of annual period data, and the empirical distributions of the annual period data adjacent in time are different; Performing a grade evaluation table generation process on all the annual periodic data to obtain a periodic evaluation table corresponding to each annual periodic data; According to the health indicator data, health mapping evaluation is performed on all the periodic evaluation tables to obtain the health evaluation results of the rivers and lakes.

2. The method according to claim 1, characterized in that: The multi-year average daily flow series set is divided into annual periods to obtain a number of annual period data, including: Get the partition threshold; Get the partition start point, partition check point and partition end point; According to the division threshold, the division starting point, the division check point and the division end point, the multi-year average daily flow sequence set is divided into annual periods to obtain a plurality of the annual period data.

3. The method according to claim 2, characterized in that According to the division threshold, the division starting point, the division check point and the division end point, the multi-year average daily flow sequence set is divided into annual cycles to obtain a plurality of annual cycle data, including: According to the division starting point and the division check point, the multi-year average daily flow sequence set is divided into a first sequence to obtain a first flow sequence; According to the division check point and the division end point, the multi-year average daily flow sequence set is divided into a second sequence to obtain a second flow sequence; According to the first traffic sequence, performing empirical distribution consistency verification on the second traffic sequence to obtain an empirical distribution verification result; According to the division threshold, performing a first threshold verification on the division termination point to obtain a first threshold verification result; If the empirical distribution verification result is that the empirical distribution is different and the first threshold verification result is that the division end point is less than the division threshold, then the first traffic sequence is retained, and the division starting point is updated according to the division check point, and the division check point and the division end point are updated after the updated division starting point, and then the steps of obtaining the division starting point, the division check point and the division end point are returned to execute; or, if the empirical distribution verification result is that the empirical distribution is different and the first threshold verification result is that the division end point is equal to the division threshold, then based on the current second traffic sequence and all the first traffic sequences, several annual period data are obtained.

4. The method according to claim 3, characterized in that: The method further comprises: If the empirical distribution verification result is that the empirical distributions are the same and the first threshold verification result is that the division end point is less than the division threshold, the division end point is updated, and then the steps of obtaining the division start point, the division check point and the division end point are returned to execute; or, If the empirical distribution verification result is that the empirical distribution is the same and the first threshold verification result is that the division end point is equal to the division threshold, then according to the division threshold, a second threshold verification is performed on the division check point to obtain a second threshold verification result.

5. The method according to claim 4, characterized in that The method further comprises: If the second threshold verification result is that the partition check point is less than the partition threshold, the partition check point is updated, and according to the updated partition check point, the partition end point is updated, and then the process of obtaining the partition start point, the partition check point and the partition end point is returned to the execution; or, If the second threshold verification result is that the division check point is equal to the division threshold, then a third traffic sequence is obtained based on the current first traffic sequence and the current second traffic sequence, and several annual periodic data are obtained based on the third traffic sequence and all previous first traffic sequences.

6. The method according to claim 1, characterized in that The annual periodic data is processed to generate a grade evaluation table to obtain a periodic evaluation table, including: Acquire a plurality of intra-year period indicator sub-data of the intra-year period data, each intra-year period indicator sub-data corresponding to a different type of river and lake health assessment indicator; Performing data analysis on all the sub-data of the annual periodic indicator to obtain the indicator mean and indicator standard deviation of each sub-data of the annual periodic indicator; The period evaluation table is obtained according to the mean values ​​of all the indicators and the standard deviations of all the indicators.

7. The method according to claim 1, characterized in that According to the health indicator data, health mapping evaluation is performed on all the periodic evaluation tables to obtain the health evaluation results of the rivers and lakes, including: According to the health indicator data, all the periodic evaluation tables are screened to obtain a target evaluation table corresponding to the health indicator data; According to the target evaluation table, the health indicator data is evaluated by assigning indicators and obtaining the health evaluation results of the rivers and lakes.

8. A river and lake health assessment system, characterized in that: include: The first processing unit is used to obtain health indicator data of rivers and lakes and a multi-year average daily flow series set; The second processing unit is used to divide the multi-year average daily flow series set into annual periods to obtain a number of annual period data, wherein the empirical distributions of the annual period data adjacent in time are different; A third processing unit is used to generate a grade evaluation table for all the intra-year periodic data to obtain a periodic evaluation table corresponding to each intra-year periodic data; The fourth processing unit is used to perform health mapping evaluation on all the periodic evaluation tables according to the health indicator data to obtain the health evaluation results of the rivers and lakes.

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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