CN113269383A

CN113269383A - Drainage basin high-quality development comprehensive evaluation method and device based on system science

Info

Publication number: CN113269383A
Application number: CN202110009315.2A
Authority: CN
Inventors: 张金良; 曹智伟; 金鑫; 李超群; 鲁俊; 罗秋实
Original assignee: Yellow River Engineering Consulting Co Ltd
Current assignee: Yellow River Engineering Consulting Co Ltd
Priority date: 2021-01-05
Filing date: 2021-01-05
Publication date: 2021-08-17
Anticipated expiration: 2041-01-05
Also published as: CN113269383B

Abstract

The disclosure relates to a comprehensive evaluation method and a device for high-quality development of a drainage basin based on system science, wherein the method comprises the following steps: determining the boundary and the structure of a research object, namely a drainage basin giant system, establishing a drainage basin comprehensive evaluation index system, and collecting and cleaning index data; calculating information entropy based on index data, performing entropy calculation of subsystems and giant systems by using an entropy weight method, and evaluating order degree evolution of each system; based on the division of an index system, distinguishing and respectively calculating positive entropy change and negative entropy change in the system, calculating the indexes related to the dissipation structure, and calculating the basin development index; and comprehensively evaluating the development quality of the basin according to the basin development index of the basin huge system and the degree of order of each part of the basin. According to the technical scheme, a river control decision theory taking a river basin development index as a decision basis is provided, the evolution state and the development quality of the river basin huge system are comprehensively evaluated, and technical support is provided for comprehensive control, system control and source control of the yellow river basin.

Description

Drainage basin high-quality development comprehensive evaluation method and device based on system science

Technical Field

The disclosure relates to the technical field of basin management, in particular to a basin high-quality development comprehensive evaluation method and device based on system science.

Background

In recent years, the development, protection and management of yellow river governance have drawn attention, and remarkable economic, social and environmental benefits are obtained in the aspects of water and sand governance, ecological protection, flood control and disaster reduction, water and soil loss, water resource utilization and the like, so that the sustainable development of the river basin economy and the society is effectively supported. However, the yellow river is a river which is silted, settled and migrated well, and the characteristics of less water and more sand and inconsistent water-sand relationship determine the long-term, difficulty and complexity of the yellow river treatment. The main problems faced by the current yellow river control work are that flood risks are still the biggest threats to the basin, the ecological environment of the basin is still fragile, the water resource guarantee situation is severe, and the development quality of the basin needs to be improved. In a new period, China establishes a new water treatment idea of 'priority of water conservation, space balance, system management and force exertion by two hands', gives new connotation, new requirements and new tasks of water treatment, and points out directions for strengthening water treatment and guaranteeing water safety. With the rapid development of the economic society of the river basin, the change of the water and sand situation and the engineering situation of the river, the increasing serious problems of the ecological environment and the transformation of the water control idea in the new period, the river control theory needs to be comprehensively promoted.

At present, the research on rivers and river channels simulates and analyzes certain natural or social phenomena, and the system range has limitations and does not include all the contents of the development of the natural, ecological environment and the human society.

Disclosure of Invention

In order to overcome the problems in the related technology, the disclosure provides a method and a device for comprehensively evaluating high-quality development of a drainage basin based on system science.

According to a first aspect of the embodiments of the present disclosure, there is provided a comprehensive evaluation method for high-quality development of a drainage basin based on system science, the method including:

determining the boundary and the structure of the river basin giant system, and establishing a river basin comprehensive evaluation index system, wherein the river basin comprehensive evaluation index system divides the river basin giant system into a river subsystem, an ecological environment subsystem and a human economic subsystem, and each subsystem comprises a plurality of evaluation indexes;

respectively collecting and cleaning index data of a plurality of evaluation indexes of each subsystem in a preset time period;

respectively calculating information entropy values of each subsystem and the giant system by using an entropy weight method based on the index data so as to evaluate the degree of order of the giant system and each subsystem according to the information entropy values;

calculating a dissipation structure index of the giant system based on the division of a basin comprehensive evaluation index system, and calculating a basin development index of the giant system according to the dissipation structure index, wherein the basin development index is used for representing the development quality and the evolution state of the basin giant system;

and comprehensively evaluating the development quality of the basin according to the basin development index of the basin huge system and the degree of order of the basin huge system and each subsystem.

In one embodiment, preferably, the evaluation index of the river subsystem includes at least one of:

the annual precipitation, the total water quantity, the incoming sand quantity, the flood passing capacity of the main river channel, the total silt flushing quantity and the incoming water and incoming sand are dispatched in a coordinated manner;

the evaluation index of the ecological environment subsystem comprises at least one of the following items:

the ecological torrent guarantee rate of the important section, the water quality standard-reaching rate of the important water functional area, and the water quality of the important tributary reaching or being superior to the III-class river length proportion, the habitat quality index, the vegetation cover index, the water network density index, the land stress index, the loess plateau water and soil loss control area and the typical region wetland area change rate;

the evaluation index of the human economic subsystem comprises at least one of the following:

the method comprises the following steps of standing population, urbanization rate, urban resident average domination income, urban average park green area, GDP growth rate, urban average GDP, third-generation occupation ratio, irrigation area, night light data, total watershed water consumption and ten-thousand-yuan industry added value water consumption.

In one embodiment, preferably, the acquiring and cleaning the index data of the plurality of evaluation indexes of the subsystems within the preset time period respectively includes:

acquiring index data of a plurality of evaluation indexes in a preset time period from databases of provinces, hydrological sites and watershed management mechanisms by adopting a method of dividing areas or river reach according to a time sequence;

determining the integrity of the index data of each evaluation index;

according to the completeness, performing data completion on the index data by adopting a corresponding data completion method to obtain complete index data, wherein the data completion method comprises the following steps: a linear interpolation method, a spline interpolation method, a lagrange interpolation method, and a gray prediction method.

In one embodiment, preferably, calculating information entropy values of the respective subsystems and the megafunctions by using an entropy weight method based on the index data to evaluate the degree of order of the megafunctions and the respective subsystems according to the information entropy values includes:

determining standard intervals for development of each evaluation index;

calculating the probability function of each evaluation index to different standard intervals in the corresponding standard interval to determine the probability function distribution of each evaluation index value;

calculating an information entropy value corresponding to each evaluation index according to the probability function distribution of each evaluation index value;

correcting the information entropy value by using a preset correction algorithm to obtain a corrected information entropy value, wherein the preset correction algorithm comprises:

wherein x represents the value of the target evaluation index to be corrected, S_xRepresents the information entropy value, S'_xRepresenting said modified information entropy value, x_midA boundary value representing the good and middle two standards of the target evaluation index,

an information entropy value representing the cut-off value.

Calculating according to the number of the evaluation indexes and the corrected information entropy value of each evaluation index to obtain the information entropy weight corresponding to the evaluation index;

carrying out weighted summation according to the corrected information entropy value of each evaluation index in each subsystem and the corresponding information entropy weight to obtain a total entropy value corresponding to the subsystem;

and evaluating the order degree evolution of each subsystem according to the total entropy value of each subsystem.

In one embodiment, preferably, calculating a dissipation structure index of the megasystem based on the division of the watershed comprehensive evaluation index system, and calculating a watershed development index of the megasystem according to the dissipation structure index includes:

based on the division of a drainage basin comprehensive evaluation index system, distinguishing and respectively calculating the positive entropy change sum and the negative entropy change sum of the giant system;

calculating a dissipation structure index of the giant system by using a Brussels model according to the positive entropy change sum and the negative entropy change sum of the giant system;

and calculating the basin development index of the giant system according to the dissipation structure index of the giant system.

In one embodiment, preferably, the method further comprises:

and displaying the order degree of the giant system and each subsystem, the basin development index of the giant system and the evaluation result of the development quality of the basin.

According to a second aspect of the embodiments of the present disclosure, there is provided a comprehensive evaluation apparatus for high-quality development of a drainage basin based on system science, the apparatus including:

the system comprises a determining module, a comprehensive evaluation index system and a comprehensive evaluation index system, wherein the determining module is used for determining the boundary and the structure of the river basin giant system and establishing the comprehensive evaluation index system of the river basin, the river basin giant system is divided into a river subsystem, an ecological environment subsystem and a human economy subsystem in the comprehensive evaluation index system of the river basin, and each subsystem comprises a plurality of evaluation indexes;

the data processing module is used for respectively acquiring and cleaning index data of a plurality of evaluation indexes of each subsystem in a preset time period;

the first calculation module is used for calculating information entropy values of each subsystem and the giant system respectively by using an entropy weight method based on the index data so as to evaluate the degree of order of the giant system and each subsystem according to the information entropy values;

the second calculation module is used for calculating a dissipation structure index of the huge system based on the division of a watershed comprehensive evaluation index system, and calculating a watershed development index of the huge system according to the dissipation structure index, wherein the watershed development index is used for representing the development quality and the evolution state of the watershed huge system;

and the evaluation module is used for comprehensively evaluating the development quality of the drainage basin according to the drainage basin development index of the drainage basin huge system and the degree of order of the drainage basin huge system and each subsystem.

According to a third aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the steps of the method according to any one of the embodiments of the first aspect.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:

in the embodiment of the invention, the river decision-making theory based on Basin Development Index (BDI) is provided by taking classical theories such as system science and information theory as guidance and combining an information entropy and dissipation structure calculation model, the evolution state and the Development quality of a Basin huge system are comprehensively evaluated, and technical support is provided for comprehensive treatment, system treatment and source treatment of the yellow river Basin.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.

FIG. 1 is an architecture diagram illustrating a yellow river basin megasystem in accordance with an exemplary embodiment.

FIG. 2 is a schematic diagram illustrating a watershed development evaluation index system according to an exemplary embodiment.

Fig. 3 is a flowchart illustrating a comprehensive evaluation method for high-quality development of a watershed based on system science according to an exemplary embodiment.

Fig. 4 is a flowchart illustrating step S301 in the comprehensive evaluation method for high-quality development of a drainage basin based on system science according to an exemplary embodiment.

Fig. 5 is a flowchart illustrating step S302 in the comprehensive evaluation method for high-quality development of a watershed based on system science according to an exemplary embodiment.

FIG. 6 is a schematic diagram illustrating a likelihood function in accordance with an exemplary embodiment.

FIG. 7 is a schematic diagram illustrating a likelihood function and an information entropy curve in accordance with an example embodiment.

FIG. 8 is a diagram illustrating a likelihood function and a curve of information entropy values after a modification calculation in accordance with an exemplary embodiment.

FIG. 9 is a schematic diagram illustrating the calculation result of the information entropy of the amount of sludges downstream of the yellow river according to an exemplary embodiment.

Fig. 10 is a flowchart illustrating a comprehensive evaluation method for high-quality development of a watershed based on system science according to an exemplary embodiment.

FIG. 11 is a schematic diagram illustrating mutations and branching in a system evolution, according to an example embodiment.

FIG. 12 is a phase diagram illustrating the evolution of a dissipative structural system according to an exemplary embodiment.

Fig. 13 is a schematic diagram illustrating the evolution of the degree of order of each subsystem and megasystem in the yellow river basin according to an exemplary embodiment.

FIG. 14 is a schematic illustration of a basin growth index evolution and growth levels, shown in accordance with an exemplary embodiment.

FIG. 15 is a schematic diagram illustrating a basin evolution index associated with historical events, according to an example embodiment.

FIG. 16 is a schematic diagram illustrating an evolution of dissipation structure related indicators of a watershed megasystem according to an exemplary embodiment.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

The present invention will be described in detail below with reference to the river basin as an example. It will be appreciated by those skilled in the art that the present invention is also applicable to any other watershed.

The yellow river is a complex huge system, and the yellow river treatment is a complex system engineering. Therefore, no matter the overall strategy and implementation scheme of yellow river management, the management strategy and engineering layout of different river reach, or the specific design and operation management of a single project, the method of the system theory and idea must be used as the overall guide in each stage of the whole life cycle of the yellow river, and the yellow river basin is used as an organic composite system to be considered comprehensively. The system management of the yellow river basin aims to maintain the basic functions of rivers, develop regional socioeconomic high quality and effectively protect three-dimensional cooperation of the ecological environment of the basin as an overall management target, and researches the overall layout of the comprehensive management of the yellow river basin and the game synergistic effect among different management measures in a multi-dimensional way.

In general, the yellow river basin system function can be considered from three aspects:

1) from the river function perspective, the yellow river is a river with complex natural conditions and extremely special river conditions, the relationship of water and sand is inconsistent, the drought wind and sand and water and soil loss disasters in upstream areas and the silt siltation and flood threats of downstream river channels seriously restrict the sustainable development of the economic society of the watershed and the related areas. In addition, the yellow river is an important water source in northwest and north China, and the development and utilization of water resources are related to national economic safety, energy safety, food safety and sustainable development of economic society in northwest and north China.

2) From the ecological environment function perspective, the yellow river basin is an ecological corridor connecting the Qinghai-Tibet plateau, the loess plateau and the North China plain, and has a plurality of national parks and national key ecological function areas such as the three-river source and the Qilian mountain. The yellow river flows through the loess plateau water and soil loss area and the five desert lands, and a plurality of wetlands are distributed along two banks of the river. The yellow river basin forms an important ecological barrier in China, and the ecological environment protection of the yellow river basin is related to the ecological safety of the basin and relevant areas.

3) From the aspect of economic development function, the yellow river basin is an important economic zone in China, the Huang-Huai-Hai plain, the Fenwei plain and the river sleeve irrigation area are main agricultural product production areas, and the basin land resources, the mineral resources and particularly the energy resources are quite rich and occupy extremely important positions in China, so that the yellow river basin is known as an energy basin in China, is an important energy source, chemical engineering, raw materials and basic industrial base in China, and has huge future development potential. Therefore, according to the functional division of the river basin, the yellow river basin huge system can be divided into a river subsystem, an ecological environment subsystem and a human economic subsystem, and the large-scale yellow river basin has numerous related elements and complex relations, and is not only interconnected but also restricted, so that how to ensure the water safety of the yellow river basin, realize the ecological protection of the yellow river basin and simultaneously promote the high-quality development of the yellow river basin is a very complex major problem. The architecture of the yellow river basin giant system is shown in figure 1.

The river subsystem takes river regulation as a key point, and mainly relates to factors in various aspects such as flood running, water sand, water resources, water engineering and the like. The silt problem of the yellow River is rare in the world, the problem of the secondary suspended River is prominent, flood control (River Health Index) is always the primary task for controlling yellow River, and River regulation of the yellow River is a complex problem related to multiple factors. The RHI selects 6 key indexes of total annual precipitation, total water volume, flood passing capacity of a main river channel, sand coming volume, total sediment volume and water coming and sand coming co-scheduling from the perspective of a system theory and by considering three aspects of water resources, flood and silt, and calculates the river health index through an information entropy and entropy weight method.

The ecological environment subsystem takes ecological protection as a key point, the yellow river basin comprises various factors such as forests, wetlands, species, water environment, water ecology and the like, is an important ecological barrier in China, is an ecological corridor for connecting a Qinghai-Tibet plateau, a loess plateau and a North China plain, has a plurality of national parks such as a three-river source and a Qilian mountain and key ecological functional areas of the country, simultaneously the yellow river flows through a water and soil loss area of the loess plateau and a sand land of five deserts, lakes and wetlands such as a Dongping lake and a Wulian sea are distributed along two banks of the river, and the wetlands of the estuarine are biologically diverse. The ecological environment is an integral body formed by various ecosystems consisting of biological communities and non-biological natural factors. For a long time, under the combined action of natural factors and human factors, the ecological environment develops and evolves in different space-time scales. The EDI (environmental evolution Index) quantitatively researches related factors such as habitat quality, vegetation coverage, land stress, water network wetland and the like from the ecological Environment protection perspective, and is a comprehensive Index for evaluating the Development quality of the watershed ecological Environment, which is obtained based on system theory, information entropy and entropy weight analysis.

The human economic subsystem comprises factors in various aspects such as population, industry, economy, culture and the like, is an important problem of high-quality development of the economy of the yellow river basin, the yellow river basin is an important economic zone in China, and the yellow river basin has a very important position in the development of the economy and the society in China. The SDI (Social Development Index) can reflect characteristics of residents in a drainage basin, measure welfare of the residents, comprehensively represent the current Development situation and growth vigor of the drainage basin economy and is indispensable content in the research of the drainage basin Social economy. From 4 angles such as population characteristics, resident living quality, economic growth level, regional industrial structure and the like, 12 socioeconomic characteristic indexes are selected, social development indexes are obtained through calculation by an information entropy and entropy weight method, and the social development evolution characteristics of the yellow river basin in nearly 40 years are quantitatively analyzed.

The RHI, the EDI and the SDI provide reference basis for representing the development quality of river subsystems, ecological environment subsystems and human economic subsystems, and are an important research part of river control decision-making theory.

In order to support the data analysis work of the mesoscopic layer and the macroscopic layer, the key work of the microscopic layer is to construct a yellow river basin giant system index system and collect index data. According to the connotation of the yellow river basin huge system and the related practices of river development evaluation at home and abroad, a basin development evaluation index system is constructed according to the requirements of ecological protection and high-quality development of the yellow river basin and is shown in figure 2.

The embodiment of the invention provides a comprehensive evaluation method for high-quality development of a drainage basin based on system science, which comprises the following steps of:

step S301, determining the boundary and the structure of the river basin giant system, and establishing a river basin comprehensive evaluation index system, wherein the river basin comprehensive evaluation index system divides the river basin giant system into a river subsystem, an ecological environment subsystem and a human economy subsystem, and each subsystem comprises a plurality of evaluation indexes.

Step S302, respectively collecting and cleaning index data of a plurality of evaluation indexes of each subsystem in a preset time period;

step S303, respectively calculating information entropy values of each subsystem and the giant system by using an entropy weight method based on the index data so as to evaluate the degree of order of the giant system and each subsystem according to the information entropy values;

step S304, calculating a dissipation structure index of the giant system based on the division of a drainage basin comprehensive evaluation index system, and calculating a drainage basin development index of the giant system according to the dissipation structure index, wherein the drainage basin development index is used for representing the development quality and the evolution state of the drainage basin giant system.

And S305, comprehensively evaluating the development quality of the basin according to the basin development index of the basin huge system and the degree of order of the basin huge system and each subsystem.

In the embodiment, a river decision-making theory taking a basin development index as a decision basis is provided by combining an information entropy and dissipation structure calculation model, the evolution state and the development quality of a basin huge system are comprehensively evaluated, and technical support is provided for comprehensive treatment, system treatment and source treatment of a yellow river basin.

As shown in fig. 4, in one embodiment, preferably, the step S302 includes:

step S401, according to the time sequence, index data of a plurality of evaluation indexes in a preset time period are obtained from databases of provinces databases, hydrological sites and watershed management mechanisms by adopting a method of dividing areas or river reach.

In this implementation, the evaluation index may be obtained from both the temporal and spatial dimensions. The time-dimension information constitutes time-series data, and the evaluation of the yellow river basin development index is limited to the influence of historical factors such as incomplete data after the establishment of new china, and the research range is set within the time scale of nearly 40 years, namely from the 80 th century. The granularity of the data needs to be uniform for all evaluation indexes and is limited by the acquirability of the data, and the annual average value is adopted in the invention.

In the spatial dimension, a method of dividing regions or river reach is adopted to collect data, and the collected data is classified into a drainage basin level. The river basin spans nine provinces, corresponding ecological and environmental data can be collected from databases of all provinces, and for professional data of rivers such as hydrology, silt and the like, internal data from hydrology sites and river basin management mechanisms are used for averaging data of different areas or typical area data represent large area data to obtain river basin level data layer by layer.

Step S402, determining the integrity of the index data of each evaluation index;

step S403, according to the completeness, performing data supplementation on the index data by adopting a corresponding data supplementation method to obtain complete index data, wherein the data supplementation method comprises the following steps: a linear interpolation method, a spline interpolation method, a lagrange interpolation method, and a gray prediction method.

In this embodiment, the data consolidated during the data collection phase is a result of recognition by various industry experts. First, collected index data is preprocessed. For example, for the evaluation of the yellow river basin development index, the required data is historical annual data of nearly 40 years. For indices with spatial differences, it is also required that the data have a complete time series within each space or region. The evaluation of the system evolution is based on the change rule of the index according to the time. After the complete time sequence of all index data is established, the addition and integration among indexes are carried out, and the evaluation indexes of the large giant system are formed step by step. For various reasons, time sequence data has certain missing phenomena, and for the missing years, different filling strategies should be adopted according to different situations:

(1) the whole piece of index data is missing. Generally, recent data is relatively complete, and early data loss is more serious, and sometimes a large amount of data is lost. At this time, a certain speculation should be made based on the general change rule and fluctuation condition of the index, and in combination with the important influence events which have occurred historically or issued major river control strategies, data of several years is preferably given as a control point. On the basis, based on the existing time series, the data of the historical years are presumed by backtracking forwards.

(2) Annual data is missing, only data that appears every few years (typically 5 years). Some indicators are not measured every year but are counted at regular intervals, which can be handled as given for the control point in the above case.

(3) Sporadically lack data for certain years. This is relatively easy to handle, and if data of a certain year is lacked in the whole time series, the average value of data of two adjacent years can be directly used for replacing the missing data, and the system evaluation result is not greatly influenced.

(4) In a few cases, the last year's data will be missing. This should be because the latest statistics have not been discharged, and the latest year data can be predicted by using the data of the recent years.

For the completion of missing data, the data processing methods mainly used include linear interpolation, spline interpolation, lagrange interpolation, gray prediction method and the like.

On the basis of expert review data, for extremely individual abnormal data (namely data noise), after determining the abnormal reason, considering various factors influencing the index, combining with expert experience comprehensive judgment, performing targeted processing on the abnormal data, and providing corrected data.

Fig. 5 is a flowchart illustrating step S303 of the comprehensive evaluation method for high-quality development of a watershed based on system science according to an exemplary embodiment.

As shown in fig. 5, in one embodiment, preferably, the step S303 includes:

step S501, determining standard intervals of development of each evaluation index;

step S502, calculating the probability function of each evaluation index to different standard intervals in the corresponding standard interval to determine the probability function distribution of each evaluation index value;

according to the grey system theory, grey numbers are a class of numerical values with ambiguous value information, and the size of the "probability" of taking different numerical value intervals can be described by a probability function (probability function). For an evaluation index system, the range of index values can be divided into several grades, and each grade represents different development levels of the index. According to the national standard, the standard rule, the internationally recognized index standard and the latest results of similar researches, the development quality of each index is divided into four grades of excellent, good, medium and poor, and then the probability function of the index standard is calculated.

Typical likelihood functions are continuous functions of left rising and right falling determined by starting and ending points, as shown in fig. 6, where l (x) is a left increasing function and r (x) is a right decreasing function.

By utilizing the probability function, for each evaluation index value, the probability functions of the value to different standard intervals can be solved, and based on the values of the functions, the information entropy value reflecting the element index development condition can be calculated. The invention adopts an improved version aiming at the standard type probability function, namely an exponential type probability function, and concretely calculates as follows:

for the 1 st standard interval:

for the kth standard interval (

k

2, 3, …. n-1):

for the nth standard interval:

wherein x represents the evaluation index value, level_k(k is 1 to n) represents a critical value of each standard interval, level1<level2<……<level-1, coef ═ n. Since n is>1, the probability function is rapidly reduced in the area outside the value range, which accords with the idea of the probability function concept. For the four established criteria of superiority, goodness, mediality, and difference, an exponential likelihood function curve can be plotted for all (theoretical) value ranges of the index, as shown in fig. 7.

The curves with four different labels in fig. 7 represent the probability function of the index value to four standard intervals. The probability function has the advantages that for a certain index value, the information contained in the index value can be fully mined by means of the set interval, and the information describes the development condition of the minimum system unit together.

Step S503, calculating an information entropy value corresponding to each evaluation index according to the probability function distribution of each evaluation index value;

in the invention, based on the probability function distribution of each evaluation index value, the information entropy value is calculated by formula 4 and formula 5.

In the

formulas

4 and 5, n represents the number of evaluation index value standard intervals, p_kRepresenting the specific gravity of each standard likelihood function value among all values. The calculation result of the entropy value and the likelihood function calculated from the index value is shown in fig. 7. It is not difficult to find from the calculation result of the probability function that when the value is larger or smaller, the probability function values corresponding to several index levels will evolve toward a more concentrated trend as the value is far away from the intermediate standard region, directly resulting in the reduction of the entropy value.

According to the discovery, in consideration of the benefit of entropy reduction on a system, the invention provides a novel information entropy calculation method by combining the property that the index is larger and better or larger and worse, and the calculation process of the entropy is corrected correspondingly, namely the calculation process of the entropy corresponding to the worse index value is corrected according to the polarity of the index. For the indexes with larger size and better quality, the entropy value corresponding to the index value smaller than the boundary value of the good standard and the medium standard can be corrected, and the calculation method is shown in formula 6. For the index of negative polarity, by a similar method, the larger value (right side) interval is correspondingly turned over, and the modified entropy curve is generally monotonically increased. The correction is uniformly carried out on all the entropy values, and the quality of system development measured by using the change rule of the entropy values cannot be influenced.

And step S504, correcting the information entropy value by using a preset correction algorithm to obtain a corrected information entropy value.

In one embodiment, preferably, the preset correction algorithm includes:

an information entropy value representing the cut-off value. The modified entropy curve is generally monotonically decreasing, see fig. 8.

Fig. 9 shows the entropy calculation result of the index "the amount of sludge flowing downstream of the yellow river". The measurement unit of the silt flushing amount is billion cubic meters, the value can be positive or negative, the positive value represents silt deposition, and the negative value represents silt erosion, so that for the silt problem, the silt flushing amount has negative polarity, namely, the smaller the silt flushing amount is, the better the silt flushing amount is, and the more orderly the system unit is. It can be seen from the figure that as the original value is reduced, the information entropy value is reduced, and the trends of the two curves are very close, that is, there is scientific evidence for measuring the development quality by using the entropy value of the index.

The entropy curve obtained after the correction by the method has smaller information entropy corresponding to an excellent value range no matter the index is larger and more excellent or larger and worse than the original value. Thus, a direct correlation is established between the merit and disadvantage of the indicator value and the effect of entropy increase and entropy decrease on the system. The information entropy can be used as an equivalent, and as a ruler, dimensions and units of all indexes in the system are unified, so that the influence of each index on the development of the system is directly quantified.

Step S505, calculating according to the number of the evaluation indexes and the corrected information entropy values of the evaluation indexes to obtain information entropy weights corresponding to the evaluation indexes;

step S506, carrying out weighted summation according to the corrected information entropy values of the evaluation indexes in the subsystems and the corresponding information entropy weights to obtain total entropy values corresponding to the subsystems;

the information entropy weight of the index is obtained by using the formula 7, and the total entropy of a certain system can be obtained by performing weighted summation on the entropy values of the indexes in the system by using the entropy values and the weights of the indexes, as shown in the formula 8.

In the

expressions

7 and 8, N represents the number of evaluation indexes to be weighted, Si and wi represent the information entropy value of the evaluation indexes and the corresponding information entropy weight, respectively, and Ssys represents the total entropy value of the system.

In this embodiment, the information entropy weight of each index can be calculated for the entire complex macro system or any subsystem therein, and then it is determined which index or indexes in the basin macro system have the greatest contribution to the system order, that is, the most important index. The information entropy is a measure of information quantity and uncertainty, and the larger the information quantity brought by a certain index is, the lower the entropy value is, the lower the uncertainty is, and the larger weight can be given to the index. The method is more scientific in calculating the index weight, and avoids the difference caused by subjective judgment of the weight by different experts. The entropy weight method has the greater significance that the weight of each index in the system changes along with the change of the information entropy value of each index, the indexes interact and dynamically interact, and the entropy weight method can monitor the real-time change of the relative importance of the indexes in the system in real time, so that the entropy weight method is very fit with the view of system governance. In guiding the management of the drainage basin, the index with larger improvement weight can be changed into a main measure or an engineering demonstration for consideration.

Although the information entropy of the subsystems and the giant systems can depict the development and change trend of the ordered degree of the systems, the state of the systems in the development process cannot be described, so that the invention further introduces a dissipation structure theory and a related model to judge the development state of the systems.

As shown in fig. 10, in one embodiment, preferably, the step S304 includes:

step S1001, based on division of a drainage basin comprehensive evaluation index system, distinguishing and respectively calculating a positive entropy change sum and a negative entropy change sum of the giant system;

step S1002, calculating dissipation structure indexes of the giant system by using a Brussels model according to the positive entropy change sum and the negative entropy change sum of the giant system;

and step S1003, calculating the basin development index of the giant system according to the dissipation structure index of the giant system.

The theory of dissipative structures was established by belgian physicochemical pril (i.primogine) in 1969. The pri-Gaojin divides a macroscopic system into three systems of an isolated 1 system, a closed 2 system and an open 3 system, wherein the open system is divided into the following systems according to the balance degree of material and energy distribution in the system: thermodynamic equilibrium, near equilibrium, and far from equilibrium. Prigazine considers that the second law of thermodynamics and statistical mechanics only express the laws of an isolated system under the conditions of an equilibrium state and a near equilibrium state. Far from the equilibrium state, an open thermodynamic system can exchange materials and energy with the external environment continuously and has nonlinear effect inside, once a certain system parameter reaches a certain threshold value, the system can possibly generate a self-organization phenomenon, and then a time, space and function high-level ordered space-time structure is achieved, namely a dissipation structure, and the system is in the state of the dissipation structure. A corresponding system evolution diagram is shown in fig. 11. The dissipation structure maintains the ordered structure by continuously exchanging substances and energy with the outside, a self-organizing and self-adapting system is formed in the dissipation process, the system not only has the capacity of resisting the outside interference, but also can reach the next 'mutation point' through continuous self-updating evolution, and the transition of the system to a higher ordered state is realized. In summary, the formation of the dissipative structure requires that four conditions are met: the system is open, the system is far away from the equilibrium state, the fluctuation exists in the system, and the nonlinear effect exists in the system.

The state of the system in the evolution process is analyzed by utilizing a dissipation structure theory, the quantitative analysis on the activity degree of the system is realized, and the dynamic characteristics, the development potential and the evolution trend of the system can be judged. The steady state of the dynamic system mainly comprises a balanced state, a periodic state, a quasi-periodic state, a chaotic state (fractal) and the like. For a system in a non-dissipative structure, the evolution of the system gradually approaches an equilibrium stationary state, and corresponding to a "dead point" or a "singularity" on a phase diagram of the system, the system parameters also converge to a certain value and do not change with time, which is the basic principle of thermodynamics in an equilibrium state and a near equilibrium state. And as shown in the phase diagram of the system in fig. 12, the state parameter is changed periodically all the time and converges to the limit cycle, that is, the system reaches the periodic steady state of the dissipation structure.

The Brussler model proposed by the Progaz university provides a method for quantitatively analyzing a dissipation structure and the activity degree of a system by analyzing a chemical cross-catalytic reaction system. Through the escape of the Brussels model, the mathematical criterion of the river system becoming the dissipation structure can also be deduced. The chemical reaction system described by the brussel model can be represented by chemical reaction formulas 13-16:

A→X (13)

B+X→Y+D (14)

Y+2X→3X (15)

X→E (16)

where A, B represents the concentration of the initial reactants, D, E represents the concentration of the reaction products, and X, Y represents the concentration of the intermediate components. The model is simplified here by variable substitution, and the reaction coefficients for each reaction are assumed to be 1. The kinetic equation of this reaction system can be expressed by equations 17 and 18:

there is a unique stationary solution (a, B) to the system of equations, i.e., the motionless or singularity. According to the research on the dynamic stability of the system, the stability analysis of the linear approximation equation should be carried out near the motionless point according to the related knowledge of the ordinary differential equation qualitative method. According to the obtained linearizationCharacteristic equation of system, curve | B | ═ 1+ a²Is the boundary between the transitions of the system singularity stability, i.e. the boundary between the states of the dissipative and non-dissipative structures. In addition, the system has a unique limit cycle as proved by the cycle domain theorem and the uniqueness theorem.

The brussel model appears simple, but can delineate all major reaction processes within the dissipative structural system. In the model, A, B was continuously input as a reactant, D, E was taken away immediately once generated, reflecting the openness of the system, while also maintaining the system away from equilibrium; the 2 nd and 3 rd reaction formulas respectively represent X, Y two intermediate product concentration-inverse game relationship, the two material stocks alternately take the initiative to form fluctuation phenomenon; the form of the 3 rd reaction formula can simulate complex nonlinear action in the system.

The invention utilizes two entropy change effects in the development process of the drainage basin, namely positive entropy change and negative entropy change to generalize all complex changes in the system, and then uses a Brussel model to evaluate the state of the system. The forward entropy change refers to that in the process of system development and evolution, the change amount of the system entropy value gradually or rapidly shows a positive state larger than zero due to the generation, accumulation and activation of contradictions inside the system or due to improper exchange of materials, energy and information between the system and the environment, so that the system generates a non-order effect. The forward entropy change causes disorder of system situation, slow development speed and low operation efficiency. The negative entropy change means that in the development and evolution process of the system, as the system and the environment perform reasonable exchange of substances, energy and information, the conditions of mutual restriction and interference among internal elements of the system are improved, contradiction is solved and weakened, so that the entropy value of the system is continuously reduced, and finally, the change amount of the entropy of the system gradually or rapidly presents a negative value state smaller than zero, so that the order effect of the system is generated. Negative entropy changes are involved or foster a stimulus for the steady and orderly development of the protective system. According to the physical significance of positive entropy change and negative entropy change, firstly, distinguishing positive entropy change indexes and negative entropy change indexes in an index system, taking the entropy value of the positive indexes as the positive entropy change value of the indexes, and taking the negative value of the index entropy value according to the symmetric value of good and medium standard critical entropy values as the negative entropy change value.

The meaning of 6 substance representatives in the Brussels model is transformed into related concepts in the watershed system respectively: A. b is the positive entropy change effect and the negative entropy change effect of the system overall respectively; D. e is two system states which can be formed under the interaction of positive entropy change and negative entropy change, wherein D is a non-dissipation structure, and E is a dissipation structure; x, Y represent the overall change of the system evolution index formed under the action of positive and negative entropy changes respectively.

The dynamics critical condition for judging the system to be a dissipation structure by the Brussels model is that | B | > 1+ A². Under the condition, the stationary solution of the equation set is converted into a form of a limit ring, and the system enters a dissipation structure state; when | B | < 1+ A²When the system is in a non-dissipative configuration, i.e., a stable thermodynamic branch; when | B | ═ 1+ A²The system is in a critical state between the two. The dissipation structure index for each time period is calculated using equation (19):

Index_DS＝|B|-(1+A²) (19)

wherein A and B represent the sum of the positive and negative entropy changes, Index, respectively, of the system_DSRepresenting a dissipative structural indicator.

In order to make the two terms of positive and negative entropy change values in equation (19) in the same domain, the negative entropy change value is enlarged by a factor of 2. The calculation according to the formula (19) shows that the value range of the dissipation structure index is in the range of [ -2,1], and the linear conversion of the range to the percentage range is performed during calculation, that is, the following conversion formula is obtained based on the linear expression between the two endpoints (-2,0) and (1, 100):

BDI＝100*(Index_DS+2)/3 (20)

then, by using the critical values and the index polarities of all the index value standard intervals, dissipation structure index values corresponding to the index critical values can be calculated to be-0.5, -0.38 and-0.23 respectively, and then the minimum dissipation index-0.5 corresponding to the index critical value is abandoned by taking the standard in consideration of the fact that the system is relatively difficult to reach the dissipation structure and is high in system development quality, and finally a system development quality evaluation score conversion table is obtained, as shown in table 1.

TABLE 1

In one embodiment, preferably, the method further comprises:

in one embodiment, preferably, the method further comprises:

show theThe evaluation results of the degree of order of the huge system and each subsystem, the basin development index of the huge system and the development quality of the basin.

Next, the development quality of the yellow river basin in the past 40 years is comprehensively evaluated by using the theoretical method system established by the present invention, and the calculation results are analyzed. The degree of order of the three subsystems in the yellow river basin megasystem is represented by the evolution curves (three dotted lines) of the three subsystem development indexes shown in fig. 13, the mean of the three indexes is represented by the black solid line, and the evolution of BDI is represented by the black solid line with the circle mark. Table 2 shows the results of the development quality index calculations for each subsystem and river basin megasystem in the yellow river basin.

The calculation result shows that the mean change trend of the development quality index evolution curves of the three sub-systems of the watershed is the same as the trend of the development index BDI of the watershed, that is to say, the development evolution of the three sub-systems jointly determines the development evolution of the whole watershed megasystem. Throughout the 40 year study interval, the mean BDI value was 58.5 points, with the lowest value being 50.5 points in 1996 and the highest value being 66.6 points in 2019. BDI, over the past 40 years, generally undergoes two phases of deterioration followed by optimization: (1) from 1980- -1996, BDI volatility decreased and the development of the watershed system overall worsened; (2) from 1997 to date, BDI gradually diminished fluctuations and progressed to better, and the development of watershed systems generally became better.

TABLE 2

From the trend of the development indexes of the three subsystems, in the 80 th 20 th century, the economic development in the watershed belongs to the starting stage, the damage to rivers and ecological environments is small, and the watershed is healthy overall. Before 1985, BDI was at a level above the mean and watershed development was relatively good. After 1985, BDI volatility decreased until the lowest value in 1996. This is due to the low quality of economic development and the resulting deterioration of the ecological environment. The yellow river basin economy as an important component of the whole national economy reflects the general trend of the national economy development, and the ecological environment protection and basin bearing capacity maintenance are not paid enough attention to the economic development, so that the system development is fluctuated and the whole system is deteriorated. After 1996, although the development volatility still exists, the general development trend of the system is better due to the reasonable application of the major water conservancy projects such as scientific treatment decision and the wave bottom, and the like, and the volatility is smaller, so that the watershed is better developed.

The evolution of BDI and the grade change of watershed development quality are shown in fig. 14 according to the numerical correspondence of BDI and development quality in table 1. It can be seen that the overall quality of development of the yellow river basin has gone through several stages of "good-medium-poor-medium-good" over 40 years and is numbered year by year over the last 10 years, approaching the "excellent" development grade. If the development trend can be kept, the scientific management and the system management of the yellow river are continuously promoted, the yellow river basin system is expected to enter a dissipation structure state, and a high-grade ordered structure of self-balance and self-organization of the system is gradually established, so that the concept of high-quality development is very met.

Further analysis is performed below in connection with significant historical events occurring in the yellow river basin. Fig. 15 demonstrates the evolution of the BDI index of the yellow river basin and the correlation of several significant events occurring within the basin. In 1982 and 1984, the yellow river has abundant water, particularly in 8 months in 1984, the yellow river has less water and sand, the water and sand relationship is relatively better in coordination, so that the river health index is better, and the BDI is greatly influenced and relatively better. In 8 months 1992, flood disasters occurred in the Wei river tributaries, and high-water-level and high-sand flood occurred at the garden mouths. In this year, the yellow river has increased in cutoff, wherein the Lijin section has cutoff for 82 days. In 1995, the yellow river was cut off all the year round for up to 122 days. In 1996 8 months, the yellow river developed 96.8 extra flood. This series of major events led to a decline in BDI until the minimum in 1996. From 1997, the yellow river basin gradually developed well with the construction and operation of a major hydro-junction. 1998-1999, Wanjiazhai and Xiaolangbei water benefit the hub to go down the gate to store water, and the yellow river water quality is scientifically dispatched uniformly for the first time to achieve the effect. During these years, the BDI value has been well developed, and even in 2000, a high quality peak was reached when the water at the bottom of the small waves was put into operation. From 2000, the yellow river achieved uninterrupted flow throughout the line and continued to develop well. Before 2010, the basin development slightly fluctuates, and after 2010, the trend of the BDI to be well-developed is more obvious, which indicates that the policy of yellow river management is more appropriate.

From the calculation result, the evolution law of the BDI index of the yellow river basin has great relevance with a plurality of major events occurring in the basin, and the influence of the major events occurring in the basin and the major change of the river water regime on the basin development is accurately simulated, which shows that the BDI calculation model adopted in the invention has considerable scientificity.

Fig. 16 shows a dissipation structure index of the watershed megasystem and a relationship between positive and negative entropy changes, and it is obvious that the dissipation structure index and the BDI development trend are the same, and since the dissipation structure index is always less than 0, it indicates that the watershed system has not reached the dissipation structure and cannot generate a self-organization phenomenon. In the period of nearly 20 years, although the yellow river basin is continuously treated and improved, the basin still has the problems of uncoordinated water-sand relationship, damaged ecological environment, low overall development quality and the like, and the yellow river is popular. This means that the river management department is required to gradually cure the disease of the yellow river by increasing the continuous inflow of the external negative entropy change while weakening the effect of the internal positive entropy change of the system.

The invention provides a unique relatively complete treatment theory and method in the field of river treatment management by improving and applying the information entropy and the dissipation structure theory. The development quality of the system is normalized to the equivalent of entropy through the concept of information entropy in the information theory, all indexes, namely the measurement of the development quality of all details of the system, are unified, and the evaluation on the order degree of the subsystem and the watershed megasystem is formed by utilizing the characteristic that entropy values can be superposed. The activity degree of the system is quantified from the aspects of system development trend and endogenous power of system evolution by combining with a dissipation structure theory. The method is a comprehensive evaluation method for the development quality of the streaming domain system, which is based on the evaluation of the order degree and scientifically judges the development quality of the system from a deeper level according to the measurement of the development state of the system.

It is further understood that the use of "a plurality" in this disclosure means two or more, as other terms are analogous. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. The singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It will be further understood that the terms "first," "second," and the like are used to describe various information and that such information should not be limited by these terms. These terms are only used to distinguish one type of information from another and do not denote a particular order or importance. Indeed, the terms "first," "second," and the like are fully interchangeable. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present disclosure.

It is further to be understood that while operations are depicted in the drawings in a particular order, this is not to be understood as requiring that such operations be performed in the particular order shown or in serial order, or that all illustrated operations be performed, to achieve desirable results. In certain environments, multitasking and parallel processing may be advantageous.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A comprehensive evaluation method for high-quality development of a drainage basin based on system science is characterized by comprising the following steps:

2. The method of claim 1,

the evaluation index of the river subsystem comprises at least one of the following items:

3. The method according to claim 1, wherein the step of respectively collecting and cleaning index data of a plurality of evaluation indexes of each subsystem in a preset time period comprises the following steps:

determining the integrity of the index data of each evaluation index;

4. The method of claim 1, wherein separately calculating information entropy values for each subsystem and the megafunctions using an entropy weight method based on the indicator data to evaluate the degree of order of the megafunctions and each subsystem according to the information entropy values comprises:

determining standard intervals for development of each evaluation index;

an information entropy value representing the cut-off value;

5. The method of claim 1, wherein calculating dissipation structure indicators of the megafunctions based on the partitioning of a basin comprehensive evaluation indicator system, and calculating basin development indices of the megafunctions according to the dissipation structure indicators comprises:

6. The method of claim 1, further comprising:

7. A comprehensive evaluation device for high-quality development of a drainage basin based on system science is characterized by comprising:

8. A computer-readable storage medium having stored thereon computer instructions, which when executed by a processor, implement the steps of the method of any one of claims 1 to 6.