Dynamic monitoring and evaluation system based on marine ecological carrying capacity

Abstract

The application discloses a dynamic monitoring and evaluation system based on marine ecological carrying capacity, relates to the technical field of marine ecological carrying capacity monitoring, and comprises an ecological monitoring module, an evaluation index calculation module, an index grading module and an ecological carrying capacity prediction module; the ecological monitoring module is used for monitoring ecological related data in the marine in real time; the evaluation index calculation module is used for calculating evaluation indexes of the marine ecological carrying capacity; the index grading module is used for evaluating the real-time state of the marine ecological carrying capacity; and the ecological carrying capacity prediction module is used for analyzing the change trend of the evaluation indexes, dynamically predicting the evaluation indexes, and performing prediction verification; the application is used for solving the problems that the existing marine ecological carrying capacity monitoring technology cannot effectively predict the marine ecological carrying capacity and the prediction result error is large, so that the marine ecological carrying capacity cannot be timely and effectively recovered.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of marine ecological carrying capacity monitoring, in particular to a dynamic monitoring and evaluation system based on marine ecological carrying capacity. BACKGROUND

[0002] As a core component of the earth's life support system, the accurate evaluation and dynamic monitoring of marine ecological carrying capacity is of great significance to sustainable development. The contradiction between marine resource development and ecological protection is becoming increasingly prominent, and innovative technical means are urgently needed to accurately quantify, real-time track and scientifically warn the ecological carrying capacity.

[0003] The existing marine ecological carrying capacity monitoring technology is usually to directly calculate the real-time marine ecological carrying capacity, but the lower the marine ecological carrying capacity, the more difficult it is to recover, and the longer the recovery period, so it is necessary to take measures when the marine ecological carrying capacity does not exceed the limit, that is, it is necessary to predict the marine ecological carrying capacity, but the prediction result of the existing marine ecological carrying capacity monitoring technology is usually a fixed value with large error, which will affect the judgment of marine ecological carrying capacity, leading to the inability to recover the marine ecological carrying capacity in time, such as the Chinese patent with the application publication number CN114493007A, which discloses "a method, device and system for evaluating the biological carrying capacity of a marine pasture", which directly calculates the biological carrying capacity, and when the biological carrying capacity is too low, it cannot take corresponding measures in time, and the existing marine ecological carrying capacity monitoring technology also has the problems of not effectively predicting the marine ecological carrying capacity and large error of the prediction result, leading to the inability to effectively recover the marine ecological carrying capacity in time. SUMMARY

[0004] The present application aims to at least solve one of the technical problems in the prior art, by monitoring the ecological related data in the ocean in real time, then integrating the ecological related data, calculating the evaluation index of marine ecological carrying capacity, calculating the lower limit of the evaluation index and calculating the grading evaluation threshold of the evaluation index, finally analyzing the change trend of the evaluation index and dynamically predicting the evaluation index and performing prediction verification, taking optimization measures in advance when the marine ecological carrying capacity is insufficient, to solve the problems of the existing marine ecological carrying capacity monitoring technology, such as not effectively predicting the marine ecological carrying capacity and large error of the prediction result, leading to the inability to effectively recover the marine ecological carrying capacity in time.

[0005] To achieve the above object, in a first aspect, the application provides a dynamic monitoring and evaluation system based on marine ecological carrying capacity, comprising an ecological monitoring module, an evaluation index calculation module, an index grading module, and an ecological carrying capacity prediction module; the ecological monitoring module, the evaluation index calculation module, and the index grading module are respectively connected with the ecological carrying capacity prediction module in data;

[0006] The ecological monitoring module is used for real-time monitoring of ecological related data in the sea;

[0007] The evaluation index calculation module is used for calculating the evaluation index of marine ecological carrying capacity through ecological related data;

[0008] The index grading module is used for establishing a grading evaluation threshold for the evaluation index, and displaying the real-time state of marine ecological carrying capacity through the grading evaluation threshold;

[0009] The ecological carrying capacity prediction module is used for analyzing the change trend of the evaluation index and dynamically predicting and verifying the evaluation index, and taking optimization measures in advance when the marine ecological carrying capacity is predicted to be insufficient.

[0010] Further, the ecological monitoring module is configured with an ecological monitoring strategy, which comprises:

[0011] The ecological related data includes seawater dissolved oxygen, biodiversity index, water body eutrophication index, pollutant emission load, and marine aquaculture density, respectively marked as Q1, Q2, Q3, Q4, and Q5, i.e. Q n , 1≤n≤5;

[0012] The seawater dissolved oxygen is monitored by a real-time monitoring buoy, the biodiversity index is obtained by biological investigation, the water body eutrophication index is obtained by laboratory analysis, the pollutant emission load is provided by the environmental protection department, and the marine aquaculture density is provided by the fishery department.

[0013] Further, the evaluation index calculation module comprises a data integration unit and an index calculation unit;

[0014] The data integration unit is used for integrating ecological related data;

[0015] The index calculation unit is used for calculating the evaluation index of marine ecological carrying capacity.

[0016] Further, the data integration unit is configured with a data integration strategy, which comprises:

[0017] The non-healthy threshold values of Q1, Q2, Q3, Q4, and Q5 are obtained, respectively marked as Min(Q1), Min(Q2), Min(Q3), Max(Q4), and Max(Q5);

[0018] The historical database is searched to obtain the maximum values of Q1, Q2 and Q3, which are marked as Max(Q1), Max(Q2) and Max(Q3) respectively, and the minimum values of Q4 and Q5, which are marked as Min(Q4) and Min(Q5) respectively.

[0019] Further, the index calculation unit is configured with an index calculation strategy, and the index calculation strategy comprises:

[0020] The parameter weights of seawater dissolved oxygen, biodiversity index, water eutrophication index, pollutant emission load and marine aquaculture density are calculated by an entropy weight method, and the parameter weights are represented by a symbol K n , K n represents the parameter weight of Q n .

[0021] An evaluation index is calculated by an evaluation index calculation formula, and the evaluation index calculation formula is , wherein IMECC is the evaluation index of marine ecological carrying capacity, and max(n) is the maximum value of n.

[0022] Further, the index grading module comprises a lower limit calculation unit and a grading setting unit.

[0023] The lower limit calculation unit is configured to calculate the index lower limit of the evaluation index.

[0024] The grading setting unit is configured to calculate the grading evaluation threshold of the evaluation index.

[0025] Further, the lower limit calculation unit is configured with a lower limit calculation strategy, and the lower limit calculation strategy comprises:

[0026] Historical ecological related data is obtained and named as ecological historical data, and the ecological related data of Q1, Q2 and Q3 less than the non-healthy threshold and the absence of Q4 and Q5 greater than the non-healthy threshold in the ecological historical data are named as normal ecological data, and the remaining ecological related data in the ecological historical data is named as abnormal ecological data.

[0027] The evaluation index of the normal ecological data is calculated and named as normal index, and the evaluation index of the abnormal ecological data is calculated and named as abnormal index.

[0028] The minimum value in the normal index and the maximum value in the abnormal index are searched and named as normal minimum index and abnormal maximum index respectively.

[0029] The average value of the normal minimum index and the abnormal maximum index is calculated to obtain the index lower limit of the evaluation index.

[0030] Further, the hierarchical setting unit is configured with a hierarchical setting strategy, the hierarchical setting strategy comprising:

[0031] marking the index level of the evaluation index less than or equal to the lower limit of the index as a first carrying level;

[0032] marking the lower limit of the index as LI, and calculating (LI+1) / 2 to obtain a carrying threshold;

[0033] marking the index level of the evaluation index greater than the lower limit of the index and less than or equal to the carrying threshold as a second carrying level, and marking the index level of the evaluation index greater than the carrying threshold as a third carrying level;

[0034] the first carrying level is less than the second carrying level, and the second carrying level is less than the third carrying level.

[0035] Further, the ecological carrying prediction module is configured with an ecological carrying prediction strategy, the ecological carrying prediction strategy comprising:

[0036] collecting ecological related data every first monitoring time length and calculating an evaluation index, and recording the time of collection as an evaluation time;

[0037] obtaining the evaluation index and the corresponding evaluation time of the first reference number of times before acquisition, numbering the evaluation index, and marking the evaluation index in the order from front to back as IM j , the corresponding evaluation time is marked as T j , j is a positive integer and j is the serial number of IM and T;

[0038] establishing a two-dimensional coordinate system with T j as the X-axis and IM j as the Y-axis, naming it as an ecological prediction coordinate system, and recording IM j in the ecological prediction coordinate system according to T j ;

[0039] setting H, marking the coordinate points (T1, IM1) to (T H , IM H ) as prediction reference points, and marking (T H+1 , IM H+1 ) to (T max(j) , IM max(j) ) as prediction verification points, wherein max(j) is the maximum value of j;

[0040] predicting and verifying the evaluation index through the prediction reference points and the prediction verification points.

[0041] Further, the predicting and verifying the evaluation index through the prediction reference points and the prediction verification points comprises:

[0042] Discrete regression analysis is performed on the prediction reference point to obtain an index prediction function;

[0043] T H+1 to T max(j) is substituted into the index prediction function, and the calculation result is marked as IP H+1 to IP max(j) ;

[0044] IM H+1 to IM max(j) , in the range of H+1≤j≤max(j), IM j / IP j is calculated, and the calculation result is marked as R j , the average value of R j greater than 1 is calculated and marked as RF;

[0045] T j corresponding to the time to be predicted is substituted into the index prediction function, and the prediction value of the evaluation index is obtained by solving, which is marked as PM, PM×RF is calculated to obtain the predicted minimum index;

[0046] If the predicted minimum index belongs to the first bearing grade, an ocean ecological carrying capacity early warning signal is output.

[0047] The present application has the following advantages: the present application monitors the ecological related data in the ocean in real time, then integrates the ecological related data, calculates the evaluation index of the ocean ecological carrying capacity, calculates the lower limit of the evaluation index and the grading evaluation threshold of the evaluation index, and the advantage is that the ecological related data usually has certain correlation, and the evaluation index usually increases or decreases when the evaluation index is calculated, so when one item of ecological related data is abnormal, the remaining ecological related data is usually also close to abnormal, so that the evaluation index when the abnormality occurs is smaller than the evaluation index when the normality occurs, and different bearing grades are divided for intuitive evaluation of the ocean ecological carrying capacity, thereby improving the accuracy and rationality of the ocean ecological carrying capacity monitoring.

[0048] The present application analyzes the change trend of the evaluation index, dynamically predicts the evaluation index, and performs prediction verification, and takes optimization measures in advance when the ocean ecological carrying capacity is predicted to be insufficient, and the advantage is that the prediction verification process is added when the evaluation index is predicted, so that the prediction index is closer to the actual value, and the accuracy and effectiveness of the ocean ecological carrying capacity monitoring are improved. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 is the principle block diagram of the system of the present application;

[0050] Figure 2 is the step flow chart of predicting the ocean ecological carrying capacity of the present application;

[0051] Figure 3 An ecological prediction coordinate system of the present application. DETAILED DESCRIPTION

[0052] It should be noted that the following detailed description is exemplary in nature and is intended to provide further description of the application. 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.

[0053] It is to be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application.

[0054] In the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0055] Embodiment 1, please refer to Figures 1 to 2 As shown in the figure, the present application provides a dynamic monitoring and evaluation system based on marine ecological carrying capacity, which includes an ecological monitoring module, an evaluation index calculation module, an index grading module, and an ecological carrying capacity prediction module. The ecological monitoring module, the evaluation index calculation module, and the index grading module are respectively connected with the ecological carrying capacity prediction module.

[0056] The ecological monitoring module is used for real-time monitoring of ecological related data in the sea;

[0057] The ecological monitoring module is configured with an ecological monitoring strategy, which includes:

[0058] The ecological related data includes seawater dissolved oxygen, biodiversity index, water eutrophication index, pollutant emission load, and marine aquaculture density, respectively marked as Q1, Q2, Q3, Q4, and Q5, i.e. Q n , 1≤n≤5;

[0059] The seawater dissolved oxygen is monitored by a real-time monitoring buoy, the biodiversity index is obtained by biological investigation, the water eutrophication index is obtained by laboratory analysis, the pollutant emission load is provided by the environmental protection department, and the marine aquaculture density is provided by the fishery department.

[0060] In practical application, Figure 2 The steps of predicting the marine ecological carrying capacity are shown in the flowchart; the seawater dissolved oxygen, the biodiversity index, the water eutrophication index, the pollutant emission load, and the marine aquaculture density can be directly obtained, and the acquisition method is not limited, among which the seawater dissolved oxygen, the biodiversity index, and the water eutrophication index are proportional to the marine ecological carrying capacity, while the pollutant emission load and the marine aquaculture density are inversely proportional to the marine ecological carrying capacity.

[0061] The evaluation index calculation module is configured to calculate the evaluation index of the marine ecological carrying capacity based on the ecological related data; the evaluation index calculation module comprises a data integration unit and an index calculation unit;

[0062] The data integration unit is configured to integrate the ecological related data;

[0063] The data integration unit is configured with a data integration strategy, and the data integration strategy comprises:

[0064] The non-healthy threshold values of Q1, Q2, Q3, Q4 and Q5 are obtained, which are marked as Min(Q1), Min(Q2), Min(Q3), Max(Q4) and Max(Q5) respectively;

[0065] The maximum values of Q1, Q2 and Q3 are obtained from the historical database, which are marked as Max(Q1), Max(Q2) and Max(Q3) respectively, and the minimum values of Q4 and Q5 are obtained, which are marked as Min(Q4) and Min(Q5) respectively;

[0066] In actual application, the non-healthy threshold value is the existing planning standard in the field of environmental protection. In the field of environmental protection, it is considered that the ecology in the sea is poor when the seawater dissolved oxygen, biodiversity index and water eutrophication index are lower than the non-healthy threshold value, and the ecology in the sea is poor when the pollutant emission load and the marine breeding density are greater than the non-healthy threshold value, that is, the minimum value required by the seawater dissolved oxygen, biodiversity index and water eutrophication index and the maximum value limited by the pollutant emission load and the marine breeding density. In this embodiment, Min(Q1), Min(Q2), Min(Q3), Max(Q4) and Max(Q5) are 5.0 mg / L, 2, 4, 300 kg / ha·year and 1500 kg / km² respectively. The maximum values of Q1, Q2 and Q3 are obtained from the historical database, that is, the maximum values of Q1, Q2 and Q3 and the minimum values of Q4 and Q5 are obtained from the historical monitoring ecological related data, and Max(Q1), Max(Q2), Max(Q3), Min(Q4) and Min(Q5) are 8 mg / L, 4, 10, 126 kg / ha·year and 890 kg / km² respectively;

[0067] The index calculation unit is configured to calculate the evaluation index of the marine ecological carrying capacity;

[0068] The index calculation unit is configured with an index calculation strategy, and the index calculation strategy comprises:

[0069] The parameter weights of seawater dissolved oxygen, biodiversity index, water eutrophication index, pollutant emission load and marine breeding density are calculated by entropy weight method, and the symbol K n represents that K nQ represents a parameter weight n of the parameter weight;

[0070] The evaluation index is calculated by evaluating the index calculation formula, and the evaluation index calculation formula is , wherein IMECC is the evaluation index of marine ecological carrying capacity, and max(n) is the maximum value of n.

[0071] In practical application, Q1 to Q5 obtained by monitoring are 6.2, 3.1, 7.2, 205 kg / ha·year and 1260 kg / km2 respectively, and the entropy weight method is the existing weight calculation algorithm, so in this embodiment, the final parameter weight is given, and K1 to K5 are 26.45%, 24.84%, 23.69%, 13.42% and 11.6% respectively, and the evaluation index of marine ecological carrying capacity obtained by this monitoring is 0.49, and the calculation result is kept to two decimal places.

[0072] The index grading module is used to establish a grading evaluation threshold for the evaluation index, and the real-time state of the marine ecological carrying capacity is displayed through the grading evaluation threshold; the index grading module includes a lower limit calculation unit and a grading setting unit;

[0073] The lower limit calculation unit is used to calculate the index lower limit of the evaluation index;

[0074] The lower limit calculation unit is configured with a lower limit calculation strategy, and the lower limit calculation strategy includes:

[0075] Obtain historical ecological related data, named ecological historical data, find Q1, Q2 and Q3 in the ecological historical data which are less than the non-healthy threshold, and there is no ecological related data of Q4 and Q5 which are greater than the non-healthy threshold, named normal ecological data, and the remaining ecological related data in the ecological historical data is named abnormal ecological data;

[0076] Calculate the evaluation index of the normal ecological data, named normal index, and calculate the evaluation index of the abnormal ecological data, named abnormal index;

[0077] Find the minimum value in the normal index and the maximum value in the abnormal index, respectively named normal minimum index and abnormal maximum index;

[0078] Calculate the average value of the normal minimum index and the abnormal maximum index to obtain the index lower limit of the evaluation index;

[0079] In practical applications, the ecological correlation data appear in a row, each row of ecological correlation data contains corresponding Q1 to Q5, as long as one of the data exists, it is marked as abnormal ecological data, otherwise it is normal ecological data, since there is a certain correlation between different ecological correlation data, for example, the increase of Q4 pollution emission will lead to a certain degree of decrease of Q1, Q2 and Q3, Q5 changes cycle is long, usually remains unchanged, so the abnormal index is much smaller than the normal index, in order to distinguish the normal index and the abnormal index, the lower limit of the index is needed as the judgment threshold, the average value of the minimum normal index and the maximum abnormal index can be obtained, the lower limit of the index in this embodiment is 0.29;

[0080] The hierarchical setting unit is used for calculating the hierarchical evaluation threshold of the evaluation index;

[0081] The hierarchical setting unit is configured with a hierarchical setting strategy, which includes:

[0082] The index level of the evaluation index less than or equal to the lower limit of the index is marked as the first bearing level;

[0083] The lower limit of the index is marked as LI, and the bearing threshold is calculated as (LI+1) / 2;

[0084] The index level of the evaluation index greater than the lower limit of the index and less than or equal to the bearing threshold is marked as the second bearing level, and the index level of the evaluation index greater than the bearing threshold is marked as the third bearing level;

[0085] The first bearing level is less than the second bearing level, and the second bearing level is less than the third bearing level;

[0086] In practical applications, the first bearing level represents that the marine ecological carrying capacity is insufficient, which has affected the normal marine ecological environment, and the marine ecology needs to be repaired immediately, the second bearing level represents that the marine ecological carrying capacity is low, and the marine ecology can be slowly recovered or maintained by reducing pollution emission and reducing marine breeding density, and the third bearing level represents that the marine ecological carrying capacity is high, and no measures need to be taken; since LI is 0.29, the bearing threshold is calculated as 0.645.

[0087] The ecological carrying capacity prediction module is used for analyzing the change trend of the evaluation index and dynamically predicting and verifying the evaluation index, and taking optimization measures in advance when the marine ecological carrying capacity is insufficient;

[0088] The ecological carrying capacity prediction module is configured with an ecological carrying capacity prediction strategy, which includes:

[0089] Ecological correlation data is collected every first monitoring time interval, and the evaluation index is calculated, and the collected time is recorded as the evaluation time.

[0090] The evaluation indexes of the first reference number before acquisition and the corresponding evaluation time are numbered and marked as IM j , and the corresponding evaluation time is marked as T j , j is a positive integer and j is the serial number of IM and T;

[0091] Please refer to Figure 3 , taking T j as the X-axis and IM j as the Y-axis to establish a two-dimensional coordinate system, named ecological prediction coordinate system, and IM j is recorded in the ecological prediction coordinate system according to T j ;

[0092] In actual application, the first monitoring time and the first reference number are set by professional personnel themselves, without fixed requirements. In the embodiment, the first monitoring time is set to 24h, that is, the evaluation is performed in sequence every day, and the first reference number is set to 14, that is, the evaluation indexes in the past two weeks are used to predict and verify the evaluation indexes of the current day and the next few days, and T j and IM j are numbered, 1≤j≤15, IM 15 represents the real-time evaluation index, and the ecological prediction coordinate system is constructed as shown in Figure 3 ;

[0093] H is set, and the coordinate points (T H ,IM H ) to (T H+1 ,IM H+1 ) are marked as prediction reference points, and (T max(j) ,IM max(j) ) to (T j ,IM j ) are marked as prediction verification points, wherein max(j) is the maximum value of j;

[0094] Discrete regression analysis is performed on the prediction reference points to obtain the index prediction function;

[0095] In actual application, H is used to divide the evaluation indexes for prediction and the evaluation indexes for verification, and is usually set to 10. This is because the maximum value of j is 15, and H is set to 10 to ensure that the evaluation indexes for prediction are twice the evaluation indexes for verification, which can ensure that the evaluation indexes for recombination are used for prediction and verification at the same time. Therefore, when 1≤j≤10, (T j ,IM j ) is a prediction reference point, and when 11≤j≤15, (T j ,IM j ) is a prediction verification point, and the index prediction function obtained by discrete regression analysis is Y=-0.0011×X2 -0.0058×X+0.7612, wherein Y is the evaluation index, X is the T corresponding to the evaluation time j ;

[0096] T H+1 is substituted into the index prediction function, and the calculation result is marked as IP max(j) ; H+1 max(j) ;

[0097] IM H+1 is obtained max(j) , and IM j / IP j is calculated in the range of H+1≤j≤max(j), and the calculation result is marked as R j . The average value of R j less than 1 is calculated and marked as RF;

[0098] T j corresponding to the time to be predicted is substituted into the index prediction function, and the prediction value of the evaluation index is obtained by solving, which is marked as PM. PM×RF is calculated to obtain the predicted minimum index;

[0099] If the predicted minimum index belongs to the first bearing level, an early warning signal of marine ecological carrying capacity is output;

[0100] In actual application, IP 11 to IP 15 are 0.56, 0.53, 0.50, 0.46 and 0.43 in turn, and IM 11 to IM 15 are 0.56, 0.53, 0.50, 0.46 and 0.43 in turn. R 11 to R 15 are 1, 0.962, 0.94, 0.978 and 1.023 in turn, wherein 0.962, 0.94 and 0.978 are less than 1. The average value of them is calculated to obtain RF as 0.96. The average value of R j less than 1 is calculated because when R j is greater than 1, it represents that the actual value is less than the predicted value, and the smaller the evaluation index is, the worse the marine ecological carrying capacity is. Therefore, the lowest value that the evaluation index may reach is predicted through RF to evaluate the worst case that may occur. Assuming that the evaluation index of tomorrow needs to be predicted, X=16 is substituted into the index prediction function, and PM is obtained as 0.39 by solving. The predicted minimum index is corrected to 0.37 through RF, and the calculation result is rounded to two decimal places. At this time, the predicted minimum index is in the second bearing level, so no early warning signal of marine ecological carrying capacity needs to be sent, but relevant departments can be notified to take some simple measures.​

[0101] Those skilled in the art will appreciate that embodiments of the present application can be readily used as a method, a system or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (or computer- readable storage media) having computer-usable program code embodied in the medium. The medium can be any available storage media that can be accessed by a computer. By way of example, and not limitation, such computer-usable storage media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other storage medium(s) that can be used to carry or store desired computer program code in the form of instructions or data structures and that can be accessed by a computer. Also, the present application can be embodied in a computer program product that can be traded as goods or merchandise, through the storage medium described above or any other suitable medium. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (or computer-readable storage media) having computer-usable program code embodied in the medium. Figure 1 The program code can be implemented in a high level Figure 1 procedures or blocks and / or functions specified in the flow

[0102] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, another division manner can be used. For example, a plurality of units or components can be combined or integrated into another system, or some features can be omitted or not executed. In addition, the coupling or direct coupling or communication connection between the units or components shown or discussed can be indirect coupling or communication connection through some communication interfaces, devices or units, which can be electrical, mechanical or other forms.

Claims

1. A dynamic monitoring and evaluation system based on marine ecological carrying capacity, characterized in that, The ecological monitoring module, the evaluation index calculation module, the index grading module and the ecological carrying capacity prediction module are connected with each other; The ecological monitoring module is used for real-time monitoring of ecological related data in the sea; the ecological related data includes seawater dissolved oxygen, biodiversity index, water eutrophication index, pollutant emission load and marine breeding density, respectively marked as Q1, Q2, Q3, Q4 and Q5, that is, Q n , 1≤n≤5; The evaluation index calculation module is configured to calculate the evaluation index of the marine ecological carrying capacity based on the ecological related data; The index grading module is configured to establish a grading evaluation threshold for the evaluation index, and display the real-time state of the marine ecological carrying capacity based on the grading evaluation threshold; The ecological carrying capacity prediction module is configured to analyze the change trend of the evaluation index, dynamically predict the evaluation index, and perform prediction verification, and take optimization measures in advance when the marine ecological carrying capacity is predicted to be insufficient; The index grading module comprises a lower limit calculation unit and a grading setting unit; The lower limit calculation unit is configured to calculate the lower limit of the evaluation index; The grading setting unit is configured to calculate the grading evaluation threshold of the evaluation index; The lower limit calculation unit is configured with a lower limit calculation strategy, and the lower limit calculation strategy comprises: Obtain historical ecological related data, named ecological historical data, find Q1, Q2 and Q3 in the ecological historical data which are less than the non-healthy threshold, and there is no ecological related data which is greater than the non-healthy threshold, named normal ecological data, and the remaining ecological related data in the ecological historical data is named abnormal ecological data; Calculate the evaluation index of the normal ecological data, named normal index, and calculate the evaluation index of the abnormal ecological data, named abnormal index; Find the minimum value in the normal index and the maximum value in the abnormal index, respectively named normal minimum index and abnormal maximum index; Calculate the average value of the normal minimum index and the abnormal maximum index to obtain the lower limit of the evaluation index; The grading setting unit is configured with a grading setting strategy, and the grading setting strategy comprises: Mark the index level of the evaluation index which is less than or equal to the lower limit of the index as the first carrying level; Mark the lower limit of the index as LI, and calculate (LI+1) / 2 to obtain a carrying threshold; Mark the index level of the evaluation index which is greater than the lower limit of the index and less than or equal to the carrying threshold as the second carrying level, and mark the index level of the evaluation index which is greater than the carrying threshold as the third carrying level; The first carrying level is less than the second carrying level, and the second carrying level is less than the third carrying level.

2. The dynamic monitoring and evaluation system based on marine ecological carrying capacity according to claim 1, characterized in that, The ecological monitoring module is configured with an ecological monitoring strategy, and the ecological monitoring strategy comprises that the seawater dissolved oxygen is monitored by a real-time monitoring buoy, the biodiversity index is obtained by biological investigation, the water body eutrophication index is obtained by laboratory analysis, the pollutant discharge load is provided by the environmental protection department, and the marine breeding density is provided by the fishery department. 3.The dynamic monitoring and evaluation system based on marine ecological carrying capacity according to claim 1, wherein, The evaluation index calculation module comprises a data integration unit and an index calculation unit; The data integration unit is configured to integrate the ecological related data; The index calculation unit is configured to calculate the evaluation index of the marine ecological carrying capacity.

4. The system according to claim 3, wherein, The data integration unit is configured with a data integration strategy, and the data integration strategy comprises: Obtaining non-health thresholds of Q1, Q2, Q3, Q4 and Q5, respectively marked as Min(Q1), Min(Q2), Min(Q3), Max(Q4) and Max(Q5); Searching a historical database to obtain maximum values of Q1, Q2 and Q3, respectively marked as Max(Q1), Max(Q2) and Max(Q3), and minimum values of Q4 and Q5, respectively marked as Min(Q4) and Min(Q5).

5. The system according to claim 4, wherein, The index calculation unit is configured with an index calculation strategy, and the index calculation strategy comprises: The entropy weight method was used to calculate the parameter weights for dissolved oxygen, biodiversity index, eutrophication index, pollutant discharge load, and marine aquaculture density in seawater, using the symbol K. n K indicates n Represents Q n Parameter weights; The evaluation index is calculated by an evaluation index calculation formula wherein, IMECC is the evaluation index of marine ecological carrying capacity, and max(n) is the maximum value of n.

6. The system for dynamic monitoring and assessment based on marine ecological carrying capacity according to claim 5, characterized in that, The ecological carrying capacity prediction module is configured with an ecological carrying capacity prediction strategy, and the ecological carrying capacity prediction strategy comprises: Ecological related data is collected every first monitoring time interval, and an evaluation index is calculated, and the collected time is recorded as an evaluation time; The evaluation indexes of the first reference number of times before acquisition and the corresponding evaluation time are numbered and marked as IM in the order from front to back according to the evaluation time j The corresponding evaluation time is marked as T j j is a positive integer and j is the serial number of IM and T; Take T j as the X axis, IM j as the Y axis to establish a two-dimensional coordinate system, named ecological prediction coordinate system, and record IM j according to T j into the ecological prediction coordinate system; Set H, mark coordinate points (T1, IM1) to (T H , IM H ) as prediction reference points, and mark (T H+1 , IM H+1 ) to (T max(j) , IM max(j) ) as prediction verification points, wherein max(j) is the maximum value of j; The evaluation index is predicted and verified through a prediction reference point and a prediction verification point.

7. The system according to claim 6, wherein, The prediction and verification of the evaluation index through the prediction reference point and the prediction verification point comprise: Discrete regression analysis is performed on the prediction reference point to obtain an index prediction function; T H+1 o T max(j) he results of the calculations are marked IP H+1 o IP max(j) ; Acquisition of IM H+1 To IM max(j) , for H+1≤j≤max(j), compute IM j / IP j , mark the result of the computation as R j , compute the average of R j values greater than 1, marked as RF; The time to be predicted corresponds to T j Substitute the index prediction function, solve to get the predicted value of the evaluation index, marked as PM, calculate PMxRF, get the predicted minimum index; If the predicted minimum index belongs to the first carrying capacity level, an early warning signal of the marine ecological carrying capacity is output.

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