CN111861193A - Construction method of plain river network water environment bearing capacity assessment and early warning index system - Google Patents
Construction method of plain river network water environment bearing capacity assessment and early warning index system Download PDFInfo
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Abstract
The application discloses a method for evaluating the bearing capacity of a plain river network water environment and constructing an early warning index system, which relates to the technical field of evaluation of the bearing capacity of the water environment and comprises the following steps: step 1, constructing a plain river network water environment bearing capacity assessment and early warning index system frame structure; step 2, constructing an index database; step 3, calculating water environment bearing capacity evaluation index data; step 4, determining the water environment bearing capacity evaluation index weight; step 5, establishing a comprehensive index evaluation model for representing the relative magnitude of the bearing capacity of the regional water environment; step 6, evaluating and calculating a comprehensive index evaluation value of the bearing capacity of the water environment; step 7, determining values and grading; and 8, comparing the value classification grades of the comprehensive index evaluation value and the water environment bearing capacity, determining the regional water environment bearing capacity state, and performing corresponding early warning report according to the value classification grades. The method and the device are easy to operate and use, and counter measures are provided after predictive analysis through evaluation and early warning of the environmental bearing capacity.
Description
Technical Field
The application relates to the technical field of water environment bearing capacity assessment, in particular to a method for assessing water environment bearing capacity of a plain river network and constructing an early warning index system.
Background
The urban water environment problem in the plain river network area is very prominent, and the treatment difficulty is higher. The main performance is as follows: the method is characterized in that the river channel occupation and river entering pollution load are high due to the high-speed development of cities; secondly, the water system has serious segmentation, poor connectivity and weak water power; thirdly, the problems of black and odorous water body and eutrophication are prominent, and the standard reaching rate of the water functional area is low. These problems have become a significant bottleneck in the continued development of cities. The water environment is used as a basic element influencing the social and economic development, and the bearing capacity and the state of the water environment play an important role in regional development. The bearing capacity evaluation of the water environment is one of the target requirements of the water pollution prevention and control action plan in China, is the premise of realizing differentiation, scientification and refinement of regional water quality target management and is an important basis for realizing the continuous improvement and stable standard reaching of the regional water environment quality.
In recent years, a large amount of research is carried out on the theory and practice aspect of the bearing capacity of the water environment by domestic scholars, and the national environmental science research institute provides a water environment bearing capacity evaluation index system frame integrating four dimensions of water resources, the water environment, water ecology, soil and land ecology service functions and the like. The Lidong beams and the like evaluate the bearing capacity of the water environment in the Ganjiang river basin, and the bearing capacity is obtained as negative bearing, and the influence degree of the bearing capacity of the water quality is large. WANG and the like utilize an SD model to research and compare the water environment bearing capacity trend of the Bos Teng lake under different scenes, and provide scientific basis for a reasonable development mode of protecting the micro-ecological environment of the Bos Teng lake; the method is centered and the like, constructs a water environment bearing capacity evaluation index system of a pressure-state-response framework, and researches the appearance and the trend of the water environment bearing capacity of Beijing city. The Zhang Yan uses BP, RBF and Elman 3 representative neural networks to respectively construct a guaranteed city water environment bearing capacity evaluation model, and carries out comparison analysis, and finally uses an evaluation model to carry out evaluation, so as to obtain the conclusion that the BP and Elman neural networks have similar performance, are obviously superior to the RBF neural networks, and are more suitable for being used as a water environment bearing capacity evaluation model. Liu Lei and the like construct a watershed water environment bearing capacity index evaluation system taking social economy, water quality and water resource quantity as criterion layers, and respectively calculate the Hutuo river watershed Shanxi segment water environment bearing capacity evaluation value in 2006 + 2015 by using an AHP method and a vector model method and analyze the dynamic change condition. The blue-Hill and the like adopt a structure entropy weight method and a mean square error decision method to carry out combined weighting, construct an urban water environment bearing capacity index system consisting of 3 subsystems of water resource environment, water pollution control and social economy bearing, and carry out comprehensive evaluation on the urban water environment bearing capacity of Wuhan.
The river basin pollution control in China has been developed for more than 30 years, the river basin water environment management is mainly in a water quality target management mode taking administrative areas as units, the transmission process of pollutants from sources to sinks is artificially split, the environmental management difficulty of upstream and downstream administrative areas is increased, and the river cannot be comprehensively managed from the river basin level; the water quality management aims at single water body pollutants, and the water ecological function is not fully known. Meanwhile, as an important means for watershed water quality target management, total amount control is centered on pollutant discharge administrative target total amount control, and total amount control and water quality response are not considered, so that the total amount control and water quality improvement effect are disjointed.
At present, the research on the bearing capacity of the water environment is mainly focused on the large-scale research of provincial regions or a certain watershed, so that the county-region scale research is very few, and the research on the bearing capacity of the water environment of the river network region county-region is rarely reported. And the existing water environment bearing capacity evaluation index system is relatively coincident with the narrow water environment capacity concept, the economic benefit of limited water environment capacity resources is not considered, and the improvement is urgently needed in contrast with the development of high-quality boosting economy with high-level protection of ecological environment proposed by the current national level.
Disclosure of Invention
In view of the above, the present application aims to provide a method for evaluating water environment bearing capacity of a plain river network and constructing an early warning index system, so as to visually judge a main factor restricting the water environment bearing capacity of a region, thereby providing an effective measure for improving the water environment bearing capacity of the region, and achieving the purpose of differentiation and fine management of regional water quality targets. The specific scheme is as follows:
a method for evaluating the bearing capacity of the water environment of a plain river network and constructing an early warning index system comprises the following steps:
step 1, constructing a plain river network water environment bearing capacity assessment and early warning index system framework structure;
step 2, constructing an index database of a water environment bearing capacity assessment and early warning index system;
step 3, calculating water environment bearing capacity evaluation index data;
step 4, determining the water environment bearing capacity evaluation index weight;
step 5, establishing a comprehensive index evaluation model representing the relative magnitude of the bearing capacity of the regional water environment;
step 6, evaluating and calculating a comprehensive index evaluation value of the bearing capacity of the water environment;
step 7, determining the value classification grade of the bearing capacity state of the water environment;
and 8, comparing the value classification grades of the comprehensive index evaluation value and the water environment bearing capacity, determining the water environment bearing capacity state of the region, and performing corresponding early warning report according to the falling value classification grades.
Preferably: in step 1, the frame structure comprises a frame structure for establishing a DPSRE model water environment bearing capacity evaluation index data, the establishment of the DPSRE model water environment bearing capacity evaluation index data frame structure comprises a remote sensing image processing method, and the method comprises the following steps:
step 1, obtaining remote sensing images in different time periods, and performing radiation correction, atmospheric correction and geometric correction on the remote sensing images through a remote sensing image processing module;
step 2, converting the grid classification result in the remote sensing image into planar vector data, and correcting the block boundary;
step 3, based on the characteristic that different ground objects have different spectrums, recognizing and extracting different ground classes aiming at the remote sensing image to obtain ground object vector diagrams of different time periods;
step 4, combining the local area soil utilization map and ground survey data to identify the area land area, the area of the area industrial land, the area of the area cultivated land, the vegetation coverage area of the river and lake bank zone, the total area of the river and lake bank zone, the water plant coverage area of the river and lake water surface, the water surface area of the river and lake and the coverage area of the regional forest and grass;
step 5, calculating the area of the specified region of the raster data through ArcGis software;
The implementation frequency of the remote sensing image processing method is at least once a year.
Preferably: in the step 1, according to the water environment characteristics of the plain river network, a driving force model, a pressure model, a state model, a response model and a benefit model are constructed to serve as an evaluation index system framework structure.
Preferably: the evaluation index system framework structure comprises the following primary indexes: a driving force index; a pressure index; a status index; a response index; a benefit index; and the evaluation index system framework structure comprises the following secondary indexes respectively positioned under the corresponding primary indexes:
population density index under the driving force index, total production value index of unit territory area and industrial output tax index of unit industrial land;
the index of the total water consumption of production in ten thousand yuan area, the index of the fertilizer application amount in unit cultivated land area and the index of the wastewater discharge amount in unit industrial production value under the pressure index;
the water quality standard-reaching rate index of the area exit section, the water resource development utilization rate index, the shore zone plant coverage rate index, the aquatic plant coverage rate index and the area forest and grass coverage rate index under the state index;
the ratio index of the ecological environment construction investment to the total production value of the area under the response index, the index of the environment supervision capacity, the index of the industrial wastewater cyclic utilization rate, the index of the urban and rural domestic sewage treatment standard reaching rate and the index of the card swiping pollution discharge popularity rate;
The revenue index of industrial output per ton of water, the revenue index of unit sewage discharge right output, the cost index of unit industrial wastewater treatment and the cost index of unit domestic sewage treatment under the benefit index.
Preferably: in the step 3, normalization processing is required to be carried out on the obtained water environment bearing capacity evaluation index data, wherein the normalization processing comprises forward index processing, reverse index processing and interval optimal index processing;
the forward index processing comprises the following calculation formula:
wherein j is a partition serial number, i is an index serial number, and XijAs a result of the original value of the value,
normalized for the Forward value, max (X)i) And min (X)i) Respectively representing the maximum value and the minimum value of the index i in the research subarea;
the reverse index processing comprises the following calculation formula:
wherein j is a partition serial number, i is an index serial number, and XijAs a result of the original value of the value,
for inverse normalized values, max (X)i) And min (X)i) Respectively representing the maximum value and the minimum value of the index i in the research subarea;
the interval optimal index processing comprises optimal value setting and forward index processing and reverse index processing which are respectively carried out on data at two ends of the optimal value.
Preferably: in step 4, the water environment bearing capacity evaluation index weight is determined by an analytic hierarchy process, wherein the analytic hierarchy process comprises the steps of determining three expert reviews in each of five fields of water resource, water environment, water ecology, water management and macro economic management, and enabling fifteen expert reviews to perform importance comparison, arrangement, analysis and determination among indexes in a questionnaire mode.
Preferably: in step 5, the comprehensive index evaluation model comprises the following calculation formula:
wherein S isWECCThe comprehensive evaluation index of the bearing capacity of the water environment is obtained; siThe standard value of the ith index in the index layer is set; omegaiThe weight of the ith index in the index layer; m is the number of indexes.
Preferably: in step 7, the value classification includes no overload, critical overload, and overload.
Preferably: in step 8, when the comprehensive index evaluation value falls into critical overload and overload, carrying out early warning report; the early warning report comprises key index early warning, bearing state early warning and index development trend prediction early warning.
Preferably: the key index early warning comprises the steps of detecting the water quality standard-reaching rate index of the area exit section, and if the water quality standard-reaching rate index of the area exit section is lower than 100%, giving an early warning that the bearing capacity of the area water environment is in an overload state;
the early warning of the bearing state comprises the steps of evaluating the bearing capacity state of the water environment in the first period of calculation, warning the critical state that the bearing capacity of the water environment is overloaded, analyzing indexes influencing the bearing capacity state of the water environment, carrying out prediction analysis on related indexes, and providing a main method and/or a way for controlling the indexes;
The index development trend prediction early warning comprises the steps of performing prediction analysis on some indexes which change remarkably in a short period due to artificial influence or seasonal influence in a water environment bearing capacity evaluation index system so as to evaluate and analyze the water environment bearing capacity change trend.
According to the scheme, the method for evaluating and early warning index system construction of the plain river network water environment bearing capacity has the following beneficial effects:
1. by following systematic, scientific, comprehensive and operability principles, combining dimensions such as social economy, water resources, water ecological environment, land functions, water management and the like, constructing an initial evaluation index system based on water environment bearing capacity evaluation standards issued by officials and related research documents, perfecting the initial evaluation index system through expert demonstration, and constructing a set of water environment bearing capacity evaluation index system of a scientific system;
2. the method comprises the steps of establishing a water environment bearing capacity assessment index system, defining water ecological function subareas, carrying out water environment bearing capacity assessment of each water ecological subarea, carrying out time-space analysis on the water environment bearing capacity of a research area, mainly comprising longitudinal comparison of time sequences and transverse comparison of space sequences, providing effective measures for improving the water environment bearing capacity of the area, promoting total amount control to be transformed from target total amount control to total amount control with the bearing capacity as a core, realizing regional water quality target differentiation and scientific management, improving the water environment quality of a basin, laying a foundation for improving and early warning the water environment bearing capacity, promoting the strategic implementation of water pollution prevention and control plan and 'five-water co-treatment' in China, and forming a scientific and reproducible long-acting water environment management mechanism which can be popularized;
3. Calculating and analyzing the water environment bearing capacity of different water ecological function zones according to a water environment quality target management mode of 'zoning, classification, grading and staging', and judging main factors restricting the water environment bearing capacity of the zone;
4. calculating the weight of 5 types of 20 secondary indexes such as driving force, pressure, state, response, benefit and the like by adopting an analytic hierarchy process through an expert scoring judgment matrix;
5. the method comprises the steps of optimizing an index system of water environment bearing capacity by constructing and fusing 5 dimensions (called SRELM model for short) such as social economy, water resources, water ecological environment, land functions, water management and the like, judging main factors restricting the regional water environment bearing capacity more intuitively, providing effective measures for improving the regional water environment bearing capacity, and realizing regional water quality target differentiation and refined management;
6. the water environment bearing capacity evaluation index system can be used for predicting and analyzing indexes which change remarkably in a short period and are influenced by human or seasonal influences so as to evaluate and analyze the change trend of the water environment bearing capacity and provide a countermeasure;
7. the index system is complete, the data acquisition and calculation method is clear, and the evaluation result is scientific and accurate.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flow chart of a method for constructing a plain river network water environment bearing capacity assessment index system disclosed in the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it should be understood that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the application, the bearing capacity of the water environment refers to the maximum supporting capacity of the regional water environment on population and economy under the conditions that the water environment function can be continuously developed and does not change or develop towards a malignant direction under certain social and economic development and environmental quality protection requirements in a certain period and region; the water ecological functional area is a geographical unit formed by dividing the land and the water body with similarity according to the structure and the process of the water ecological system on different scales and the requirement of maintaining the integrity of the ecological system; the water environment capacity refers to the maximum allowable pollutant carrying capacity of a water area in unit time on the premise of a given water area range, environmental water condition, specified pollution discharge mode and water quality target; the exit section refers to a water quality monitoring section arranged at the junction of two areas when the water flow of the water system in the evaluation area moves to the next area.
The following specifically explains a method for constructing the plain river network water environment bearing capacity evaluation index system according to the embodiment of the present invention:
as shown in fig. 1, a method for constructing a plain river network water environment bearing capacity assessment and early warning index system includes the following steps:
step 1, constructing a plain river network water environment bearing capacity assessment index system frame structure: firstly, constructing a driving force, pressure, state, response and benefit model as an evaluation index system framework structure according to the water environment characteristics of the plain river network; the evaluation index architecture comprises the following first-level indexes: a driving force index; a pressure index; a status index; a response index; a benefit index; meanwhile, the evaluation index system framework structure also comprises the following secondary indexes respectively positioned under the corresponding primary indexes:
population density index under the driving force index, total production value index of unit territory area and industrial output tax index of unit industrial land;
the index of the total water consumption of production in ten thousand yuan area, the index of the fertilizer application amount in unit cultivated land area and the index of the wastewater discharge amount in unit industrial production value under the pressure index;
the water quality standard-reaching rate index of the area exit section, the water resource development utilization rate index, the shore zone plant coverage rate index, the aquatic plant coverage rate index and the area forest and grass coverage rate index under the state index;
The ratio index of the ecological environment construction investment to the total production value of the area under the response index, the index of the environment supervision capacity, the index of the industrial wastewater cyclic utilization rate, the index of the urban and rural domestic sewage treatment standard reaching rate and the index of the card swiping pollution discharge popularity rate;
a per ton water industrial output tax index, a unit pollution discharge right output tax index, a unit industrial wastewater treatment cost index and a unit domestic sewage treatment cost index under the benefit index;
and establishing a DPSRE model water environment bearing capacity evaluation index data frame structure, wherein the establishment of the DPSRE model water environment bearing capacity evaluation index data frame structure comprises a remote sensing image processing method, and the method comprises the following steps:
step 1, obtaining remote sensing images in different time periods, and performing radiation correction, atmospheric correction and geometric correction on the remote sensing images through a remote sensing image processing module;
step 2, converting the grid classification result in the remote sensing image into planar vector data, and correcting the block boundary;
step 3, based on the characteristic that different ground objects have different spectrums, recognizing and extracting different ground classes aiming at the remote sensing image to obtain ground object vector diagrams of different time periods;
step 4, combining the local area soil utilization map and ground survey data to identify the area land area, the area of the area industrial land, the area of the area cultivated land, the vegetation coverage area of the river and lake bank zone, the total area of the river and lake bank zone, the water plant coverage area of the river and lake water surface, the water surface area of the river and lake and the coverage area of the regional forest and grass;
Step 5, calculating the area of the specified region of the raster data through ArcGis software;
the implementation frequency of the remote sensing image processing method is at least once a year;
step 2, constructing an index database of a water environment bearing capacity evaluation index system according to the step 1;
step 3, calculating water environment bearing capacity evaluation index data; carrying out normalization processing on the obtained water environment bearing capacity evaluation index data; the normalization processing comprises forward index processing, reverse index processing and interval optimal index processing;
the forward direction index processing comprises the following calculation formula:
wherein j is a partition serial number, i is an index serial number, and XijAs a result of the original value of the value,
normalized for the Forward value, max (X)i) And min (X)i) Respectively representing the maximum value and the minimum value of the index i in the research subarea;
the reverse index processing comprises the following calculation formula:
wherein j is a partition serial number, i is an index serial number, and XijAs a result of the original value of the value,
for inverse normalized values, max (X)i) And min (X)i) Respectively representing the maximum value and the minimum value of the index i in the research subarea;
the interval optimal index processing comprises optimal value setting and forward index processing and reverse index processing which are respectively carried out on data at two ends of the optimal value;
Step 4, determining the water environment bearing capacity evaluation index weight:
determining the water environment bearing capacity evaluation index weight by adopting an analytic hierarchy process; the hierarchical analysis method comprises the steps of firstly determining three expert reviews in each of five fields of water resource, water environment, water ecology, water management and macroscopic economy management, and then carrying out importance comparison, sorting, analysis and determination on indexes by making fifteen expert reviews in total in a questionnaire form;
step 5, establishing a comprehensive index evaluation model for representing the relative magnitude of the water environment bearing capacity of the region:
and the comprehensive index evaluation model comprises the following calculation formula:
wherein S isWECCThe comprehensive evaluation index of the bearing capacity of the water environment is obtained; siThe standard value of the ith index in the index layer is set; omegaiThe weight of the ith index in the index layer; m is the number of indexes;
step 6, determining the value classification grade of the bearing capacity of the water environment:
grading the values to include no overload, critical overload and overload;
step 7, evaluating and calculating a comprehensive index evaluation value of the bearing capacity of the water environment;
step 8, comparing the value classification grades of the comprehensive index evaluation value and the water environment bearing capacity, and performing corresponding early warning report according to the falling value classification grades;
It should be noted that, when the comprehensive index evaluation value falls into the critical overload and the overload, the early warning report is performed; the early warning report comprises key index early warning, bearing state early warning and index development trend prediction early warning;
the key index early warning comprises the steps of detecting the water quality standard-reaching rate index of the area exit section, and if the water quality standard-reaching rate index of the area exit section is lower than 100%, giving an early warning that the bearing capacity of the area water environment is in an overload state;
the early warning of the bearing state comprises the steps of evaluating the bearing capacity state of the water environment in the last period of calculation, warning the critical state that the bearing capacity of the water environment is overloaded, analyzing indexes influencing the bearing capacity state of the water environment, carrying out predictive analysis on related indexes, and providing a main method and/or a way for controlling the indexes;
the index development trend prediction early warning comprises the step of performing prediction analysis on some indexes which change remarkably in a short period due to artificial influence or seasonal influence in a water environment bearing capacity evaluation index system so as to evaluate and analyze the water environment bearing capacity change trend.
Example one
As shown in fig. 1, a method for constructing a plain river network water environment bearing capacity assessment and early warning index system includes the following steps:
Step 1, constructing a plain river network water environment bearing capacity assessment index system frame structure: firstly, constructing a driving force, pressure, state, response and benefit model as an evaluation index system framework structure according to the water environment characteristics of the plain river network; the evaluation index architecture comprises the following first-level indexes: a driving force index; a pressure index; a status index; a response index; a benefit index; meanwhile, the evaluation index system framework structure also comprises the following secondary indexes respectively positioned under the corresponding primary indexes:
population density index under the driving force index, total production value index of unit territory area and industrial output tax index of unit industrial land;
the index of the total water consumption of production in ten thousand yuan area, the index of the fertilizer application amount in unit cultivated land area and the index of the wastewater discharge amount in unit industrial production value under the pressure index;
the water quality standard-reaching rate index of the area exit section, the water resource development utilization rate index, the shore zone plant coverage rate index, the aquatic plant coverage rate index and the area forest and grass coverage rate index under the state index;
the ratio index of the ecological environment construction investment to the total production value of the area under the response index, the index of the environment supervision capacity, the index of the industrial wastewater cyclic utilization rate, the index of the urban and rural domestic sewage treatment standard reaching rate and the index of the card swiping pollution discharge popularity rate;
A per ton water industrial output tax index, a unit pollution discharge right output tax index, a unit industrial wastewater treatment cost index and a unit domestic sewage treatment cost index under the benefit index;
and the following table was established:
TABLE 1DPSRE model water environment bearing capacity evaluation index data frame structure
The remote sensing image data are obtained by adopting a remote sensing image processing method, and the remote sensing image processing method comprises the following steps:
step 1, obtaining remote sensing images in different time periods, and performing radiation correction, atmospheric correction and geometric correction on the remote sensing images through a remote sensing image processing module;
step 2, converting the grid classification result in the remote sensing image into planar vector data, and correcting the block boundary;
step 3, based on the characteristic that different ground objects have different spectrums, recognizing and extracting different ground classes aiming at the remote sensing image to obtain ground object vector diagrams of different time periods;
step 4, combining the local area soil utilization map and ground survey data to identify the area land area, the area of the area industrial land, the area of the area cultivated land, the vegetation coverage area of the river and lake bank zone, the total area of the river and lake bank zone, the water plant coverage area of the river and lake water surface, the water surface area of the river and lake and the coverage area of the regional forest and grass;
Step 5, calculating the area of the specified region of the raster data through ArcGis software;
the implementation frequency of the remote sensing image processing method is at least once a year;
step 2, constructing an index database of a water environment bearing capacity evaluation index system according to the step 1;
step 3, calculating water environment bearing capacity evaluation index data; carrying out normalization processing on the obtained water environment bearing capacity evaluation index data; the normalization processing comprises forward index processing, reverse index processing and interval optimal index processing;
the forward direction index processing comprises the following calculation formula:
wherein j is a partition serial number, i is an index serial number, and XijAs a result of the original value of the value,
normalized for the Forward value, max (X)i) And min (X)i) Respectively representing the maximum value and the minimum value of the index i in the research subarea;
the reverse index processing comprises the following calculation formula:
wherein j is a partition serial number, i is an index serial number, and XijAs a result of the original value of the value,
for inverse normalized values, max (X)i) And min (X)i) Respectively representing the maximum value and the minimum value of the index i in the research subarea;
the interval optimal index processing comprises optimal value setting and forward index processing and reverse index processing which are respectively carried out on data at two ends of the optimal value;
The normalization process is judged as follows:
TABLE 2 Water Environment bearing Capacity evaluation index normalization Interval value
Wherein, the number in the brackets of each index is the weight of the index at the current level relative to the index at the previous level; the sign of "+" is indicated as a positive indicator, "-" is indicated as a negative indicator, "+ -" is indicated as an interval best indicator;
step 4, determining the water environment bearing capacity evaluation index weight:
determining the water environment bearing capacity evaluation index weight by adopting an analytic hierarchy process; the hierarchical analysis method comprises the steps of firstly determining three expert reviews in each of five fields of water resource, water environment, water ecology, water management and macroscopic economy management, and then carrying out importance comparison, sorting, analysis and determination on indexes by making fifteen expert reviews in total in a questionnaire form;
and obtaining the water environment bearing capacity evaluation index weight as the following table:
TABLE 3 evaluation index weight of DPSRE model water environment bearing capacity
Step 5, establishing a comprehensive index evaluation model for representing the relative magnitude of the water environment bearing capacity of the region:
and the comprehensive index evaluation model comprises the following calculation formula:
wherein S isWECCThe comprehensive evaluation index of the bearing capacity of the water environment is obtained; siThe standard value of the ith index in the index layer is set; omega iThe weight of the ith index in the index layer; m is the number of indexes;
step 6, evaluating and calculating a comprehensive index evaluation value of the bearing capacity of the water environment;
step 7, determining the value classification grade of the bearing capacity of the water environment:
grading the values to include no overload, critical overload and overload;
as in the following table:
table 4 comprehensive evaluation grade division of bearing capacity of water environment
| Bearer class | Not overloaded | Critical overload | Overload protection device |
| Comprehensive evaluation value (S)WECC) | 0.7～1 | 0.5～0.7 | 0～0.5 |
Step 8, comparing the value classification grades of the comprehensive index evaluation value and the water environment bearing capacity, and performing corresponding early warning report according to the falling value classification grades;
it should be noted that, when the comprehensive index evaluation value falls into the critical overload and the overload, the early warning report is performed; the early warning report comprises key index early warning, bearing state early warning and index development trend prediction early warning;
the key index early warning comprises the steps of detecting the water quality standard-reaching rate index of the area exit section, and if the water quality standard-reaching rate index of the area exit section is lower than 100%, giving an early warning that the bearing capacity of the area water environment is in an overload state;
the early warning of the bearing state comprises the steps of evaluating the bearing capacity state of the water environment in the last period of calculation, warning the critical state that the bearing capacity of the water environment is overloaded, analyzing indexes influencing the bearing capacity state of the water environment, carrying out predictive analysis on related indexes, and providing a main method and/or a way for controlling the indexes;
The index development trend prediction early warning comprises the step of performing prediction analysis on some indexes which change remarkably in a short period due to artificial influence or seasonal influence in a water environment bearing capacity evaluation index system so as to evaluate and analyze the water environment bearing capacity change trend.
Example two
The difference between the second embodiment and the first embodiment is that the first-level index, the second-level index and the weight thereof in the second embodiment are shown in the following table:
TABLE 5 SRELM model water environment bearing capacity evaluation index and weight thereof
Wherein: in the indexes, "+" indicates a forward index, "-" indicates a reverse index, "+ -" indicates an interval optimal index, and the index is marked as a key index and does not participate in the calculation of the bearing capacity of the water environment.
The experimental method comprises the following steps:
adopts the land A of Hangjia lake plain in the region of Zhongchang triangle. The A land is used as a plain river network region city, and the water ecological functional subarea III consists of 2 streets. In 2018, the three subareas share 129821 people, industrial enterprises mainly use the chemical fiber fabric dyeing and finishing industry, the total industrial production value is 7.37 million yuan, and the industrial wastewater discharge amount is 70.96 million tons. The agricultural crop planting mainly comprises wheat, rice and vegetables.
And (3) collecting and sorting the statistical data of the partition A in 2018, and evaluating the bearing capacity of the water environment of the partition A by adopting a DPSRE model of a system structure of driving force, pressure, state, response and benefit, wherein index values are shown in a table 6. And calculating the bearing capacity of the three-water environment of the 2018-year subarea to be 0.617 according to the evaluation index weight, wherein the water environment bearing capacity belongs to an overload state because the standard reaching rate of the water quality of the control section in the area is not 100 percent. The benefit index of the subarea III has obvious advantages, but the state index is low, which also influences the water quality of the exit section to a certain extent, thereby causing the overload of the bearing capacity of the water environment.
Table 62018 evaluation index value for bearing capacity of three partitioned water environments
In order to evaluate the bearing capacity of the water environment in three different water periods (rich, flat and dry water periods) in a division of 2018, evaluation index values of the different water periods need to be determined. When the water environment bearing capacity of each water ecological function partition in different water periods such as rich, flat and dry is calculated, in the water environment bearing capacity evaluation indexes of each ecological function partition in 2018, except that 5 indexes such as P2 (fertilizer application amount in unit arable area), S0 (water quality standard reaching rate of area exit section), S1 (water resource development utilization rate), S2 (bank zone plant coverage rate) and S3 (aquatic plant coverage rate) are obviously changed in different water periods, the other indexes are not obviously changed or are not changed. Therefore, by conducting the survey of the change condition of the above-mentioned index in different water periods, the survey statistics of the above-mentioned index in different water periods in 2018 are obtained and are shown in table 7.
TABLE 72018 index values for three different water periods in different divisions
In 2018, the three high water periods and the horizontal water periods of the subareas are in a non-overload state, the water environment bearing capacity is directly judged to be overloaded due to the fact that the water quality standard reaching rate of the exit section does not reach 100% in the dry water period, and the evaluation result shows that the water environment bearing capacity state of the subarea three in each water period is obviously changed, and the reason is mainly influenced by the water amount (water resource development utilization rate). Therefore, the local government can take measures in advance before the water shortage period comes, such as regulating and controlling a sluice, advocating reduction of the use amount of pesticides and fertilizers or adjustment of the use time, regulation of bank side bands, planting of aquatic plants, improvement of water ecology and the like.
And in the third division in 2018, social economic index, water resource index, water ecological environment index, land function index and water management index which are evaluated based on the SRELM model are respectively 0.774, 0.655, 0.621, 0.567 and 0.628, and are consistent with the evaluation result of the DPSRE model, because the water quality standard reaching rate of the exit section does not reach 100%, the water environment bearing capacity exceeds the standard.
Meanwhile, some indexes which change remarkably in a short period and are influenced by human factors or seasonality in the water environment bearing capacity evaluation index system can be subjected to prediction analysis to evaluate the change trend of the bearing capacity of the analyzed water environment, so that whether the water environment bearing capacity state of the region is overloaded or not is predicted, and a countermeasure is provided.
In summary, the method for constructing the water environment bearing capacity assessment and early warning index system of the plain river network provided by the application realizes accurate assessment and early warning of the environment bearing capacity by using the unique calculation method provided by the embodiment, further provides a countermeasure after predictive analysis, follows the principles of systematicness, scientificity, comprehensiveness and operability, integrates social economy, water resources, water ecological environment, land functions and water management dimensions, constructs an initial assessment index system based on the water environment bearing capacity evaluation standard issued by the official part and related research documents, perfects the initial assessment index system through expert demonstration, and constructs a set of water environment bearing capacity assessment index system of a scientific system. Correspondingly, through the constructed assessment index system for the water environment bearing capacity of the plain river network, water ecological function partitions are defined, water environment bearing capacity assessment of each water ecological partition is carried out, time-space analysis of the water environment bearing capacity is carried out on a research area, the time-space analysis mainly comprises longitudinal comparison of time sequences and transverse comparison of space sequences, effective measures for improving the water environment bearing capacity of the area are provided, total quantity control is promoted to be converted from target total quantity control to total quantity control with the bearing capacity as a core, regional water quality target differentiation and scientific management are realized, the water environment quality of a drainage basin is improved, a foundation is laid for improving and early warning the water environment bearing capacity, a water pollution prevention and control plan and 'five-water co-treatment' strategic implementation of China are promoted, and a set of scientific, popularizable and reproducible long-acting water environment management mechanism is formed.
References in this application to "first," "second," "third," "fourth," etc., if any, are intended to distinguish between similar elements and not necessarily to describe a particular order or sequence. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments described herein are capable of operation in other sequences than illustrated or otherwise described herein. Furthermore, the terms "comprises" and "comprising," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, or apparatus.
It should be noted that the descriptions in this application referring to "first", "second", etc. are for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be based on the realization of those skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present application.
The principle and the implementation of the present application are explained herein by applying specific examples, and the above description of the embodiments is only used to help understand the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific implementation and application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. A method for building a plain river network water environment bearing capacity assessment and early warning index system is characterized by comprising the following steps:
step 1, constructing a plain river network water environment bearing capacity assessment and early warning index system frame structure;
step 2, constructing an index database of a water environment bearing capacity assessment and early warning index system;
step 3, calculating water environment bearing capacity evaluation index data;
step 4, determining the water environment bearing capacity evaluation index weight;
step 5, establishing a comprehensive index evaluation model for representing the relative magnitude of the bearing capacity of the regional water environment;
step 6, evaluating and calculating a comprehensive index evaluation value of the bearing capacity of the water environment;
step 7, determining the value classification grade of the bearing capacity state of the water environment;
and 8, comparing the value classification grades of the comprehensive index evaluation value and the water environment bearing capacity, determining the water environment bearing capacity state of the region, and performing corresponding early warning report according to the falling value classification grades.
2. The method for building the plain river network water environment bearing capacity assessment and early warning index system according to claim 1, wherein in step 1, the frame structure comprises a frame structure for building DPSRE model water environment bearing capacity assessment index data, the frame structure for building the DPSRE model water environment bearing capacity assessment index data comprises a remote sensing image processing method, and the method comprises the following steps:
step 1, obtaining remote sensing images in different time periods, and performing radiation correction, atmospheric correction and geometric correction on the remote sensing images through a remote sensing image processing module;
step 2, converting the grid classification result in the remote sensing image into planar vector data, and correcting the block boundary;
step 3, based on the characteristic that different ground objects have different spectrums, recognizing and extracting different ground classes aiming at the remote sensing image to obtain ground object vector diagrams of different time periods;
step 4, combining the local area soil utilization map and ground survey data to identify the area land area, the area of the area industrial land, the area of the area cultivated land, the vegetation coverage area of the river and lake bank zone, the total area of the river and lake bank zone, the water plant coverage area of the river and lake water surface, the water surface area of the river and lake and the coverage area of the regional forest and grass;
Step 5, calculating the area of the specified region of the raster data through ArcGis software;
the implementation frequency of the remote sensing image processing method is at least once a year.
3. The method for constructing the plain river network water environment bearing capacity assessment and early warning index system according to claim 2, wherein in step 1, a driving force, pressure, state, response and benefit model is constructed as an assessment index system frame structure according to plain river network water environment characteristics.
4. The method for constructing the plain river network water environment bearing capacity assessment and early warning index system according to claim 3, wherein the assessment index system framework structure comprises the following primary indexes: a driving force index; a pressure index; a status index; a response index; the benefit index, and the evaluation index system framework structure comprises the following secondary indexes respectively positioned under the corresponding primary indexes:
population density index under the driving force index, total production value index of unit territory area and industrial output tax index of unit industrial land;
the index of the total water consumption of production in ten thousand yuan area, the index of the fertilizer application amount in unit cultivated land area and the index of the wastewater discharge amount in unit industrial production value under the pressure index;
The water quality standard-reaching rate index of the area exit section, the water resource development utilization rate index, the shore zone plant coverage rate index, the aquatic plant coverage rate index and the area forest and grass coverage rate index under the state index;
the ratio index of the ecological environment construction investment to the total production value of the area under the response index, the index of the environment supervision capacity, the index of the industrial wastewater cyclic utilization rate, the index of the urban and rural domestic sewage treatment standard reaching rate and the index of the card swiping pollution discharge popularity rate;
the revenue index of industrial output per ton of water, the revenue index of unit sewage discharge right output, the cost index of unit industrial wastewater treatment and the cost index of unit domestic sewage treatment.
5. The method for building the plain river network water environment bearing capacity assessment and early warning index system according to claim 1, is characterized in that: in the step 3, normalization processing is required to be carried out on the obtained water environment bearing capacity evaluation index data, wherein the normalization processing comprises forward index processing, reverse index processing and interval optimal index processing;
the forward index processing comprises the following calculation formula:
wherein j is a partition serial number, i is an index serial number, and XijAs a result of the original value of the value,
is a forward normalized value, max (X) i) And min (X)i) Respectively representing the maximum value and the minimum value of the index i in the research subarea;
the reverse index processing comprises the following calculation formula:
wherein j is a partition serial number, i is an index serial number, and XijAs a result of the original value of the value,
as a reversal standardChange value, max (X)i) And min (X)i) Respectively representing the maximum value and the minimum value of the index i in the research subarea;
the interval optimal index processing comprises optimal value setting and forward index processing and reverse index processing which are respectively carried out on data at two ends of the optimal value.
6. The method for building the plain river network water environment bearing capacity assessment and early warning index system according to claim 1, is characterized in that: in step 4, the water environment bearing capacity evaluation index weight is determined by an analytic hierarchy process, wherein the analytic hierarchy process comprises the steps of determining three expert reviews in each of five fields of water resource, water environment, water ecology, water management and macro economic management, and enabling fifteen expert reviews to perform importance comparison, sorting, analysis and determination among indexes in a questionnaire mode.
7. The method for building the plain river network water environment bearing capacity assessment and early warning index system according to claim 1, is characterized in that: in step 5, the comprehensive index evaluation model comprises the following calculation formula:
Wherein S isWECCThe comprehensive evaluation index of the bearing capacity of the water environment is obtained; siThe standard value of the ith index in the index layer; omegaiThe weight of the ith index in the index layer; m is the number of indexes.
8. The method for building the plain river network water environment bearing capacity assessment and early warning index system according to claim 1, is characterized in that: in step 7, the value classification includes no overload, critical overload, and overload.
9. The method for building the plain river network water environment bearing capacity assessment and early warning index system according to claim 8, is characterized in that: in step 8, when the comprehensive index evaluation value falls into critical overload and overload, carrying out early warning report; the early warning report comprises key index early warning, bearing state early warning and index development trend prediction early warning.
10. The method for building the plain river network water environment bearing capacity assessment and early warning index system according to claim 9, is characterized in that:
the key index early warning comprises the steps of detecting the water quality standard-reaching rate index of the area exit section, and if the water quality standard-reaching rate index of the area exit section is lower than 100%, giving an early warning that the bearing capacity of the area water environment is in an overload state;
The early warning of the bearing state comprises the steps of evaluating the bearing capacity state of the water environment in the first period of calculation, warning the critical state that the bearing capacity of the water environment is overloaded, analyzing indexes influencing the bearing capacity state of the water environment, carrying out prediction analysis on related indexes, and providing a main method and/or a way for controlling the indexes;
the index development trend prediction early warning comprises the step of carrying out prediction analysis on some indexes which change obviously in a short period and are influenced by human or seasonality in a water environment bearing capacity evaluation index system so as to evaluate and analyze the change trend of the water environment bearing capacity.
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