CN111563643A - A data processing method of water environment index - Google Patents

Abstract

The embodiment of the invention provides a water environment index data processing method, which comprises the following steps: determining an industrial pollution intensity index, an agricultural pollution intensity index, a town living pollution intensity index and a city non-point source pollution intensity index of a target water area; and generating a water environment index data set. The scheme of the invention provides a water environment index data processing method, which can provide an accurate data processing method for the water environment index so as to more accurately evaluate the bearing capacity of the water environment and prevent the human society from causing irreversible damage to the natural environment.

Description

A data processing method of water environment index

technical field

The invention relates to the technical field of data processing, in particular to a method for processing water environment index data.

Background technique

Due to the high concentration of population, rapid economic development, limited resource and environmental carrying capacity and special geographical conditions, it is facing a severe situation of tightening resource constraints and ecosystem degradation. Especially in the water environment, water resources are scarce. Although the discharge of water pollutants has been declining year by year in recent years, compared with the capacity of the water environment, the discharge of pollutants in some areas has exceeded the maximum allowable discharge of the water environment. The discharge of pollutants far exceeds the environmental capacity, and the water quality of many rivers exceeds the standard. In order to make the social environment develop sustainably, it is necessary to control and manage the water environment in a refined manner, and break away from the status quo of extensive management. Therefore, technologies for accurate analysis and processing of various data of the water environment are urgently needed.

SUMMARY OF THE INVENTION

The present invention provides a water environment index data processing method for finely analyzing and processing water environment data.

In order to solve the above technical problems, the technical problem solved by the present invention is to provide a water environment index data processing method, so as to avoid the problem of inaccurate judgment results of water environment carrying capacity caused by extensive data processing.

In view of the above problems, the technical problem solved by the present invention is to provide a water environment index data processing method, comprising:

Determine the industrial pollution intensity index, agricultural pollution intensity index, urban domestic pollution intensity index, and urban non-point source pollution intensity index of the target water area;

Generate a water environment index dataset.

In some embodiments, the determining of the industrial pollution intensity index includes: determining the industrial pollution intensity index B1 through pollutants discharged by the industry:

In some embodiments, the determining of the agricultural pollution intensity index includes: determining the agricultural pollution intensity index B2 through pollutants discharged from agriculture:

In some embodiments, the determining the urban non-point source pollution intensity index includes: determining the urban domestic pollution intensity index B3 through the pollutants discharged by urban life:

In some embodiments, the determining the urban domestic pollution intensity index includes: determining the urban domestic pollution intensity index B4 through pollutants discharged from urban non-point sources:

In some embodiments, the determining the urban domestic pollution intensity index includes: the calculation formula of the urban non-point source pollutant discharge is as follows:

G _total = ∑G _i ×10 ^-3

G _total - urban non-point source pollutant discharge, ton/year; G _i - annual pollutant amount of each underlying surface, kg/year, urban underlying surface is divided into roof, traffic road, green space and comprehensive land.

In some embodiments, the amount of contamination on each underlying surface is calculated by the following formula:

G _i =0.01αφPSEMC

In the formula: α—runoff correction coefficient; φ—runoff coefficient of drainage area; P—annual precipitation, mm/

year; S—area of each underlying surface, hectares; EMC—event average concentration, mg/L.

The above-mentioned scheme of the present invention at least includes the following beneficial effects:

The above solution of the present invention proposes a water environment index data processing method. By establishing a water environment index data set, an accurate data processing method can be provided for the water environment index, so as to more accurately evaluate the water environment carrying capacity, Prevent human society from causing irreversible damage to the natural environment.

Description of drawings

FIG. 1 is a schematic flowchart of a water environment index data processing method in an embodiment of the present invention.

Detailed ways

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure will be more thoroughly understood, and will fully convey the scope of the present disclosure to those skilled in the art.

As shown in Figure 1, the embodiment of the present invention provides a kind of processing method of water environment index data, including:

(1) Industrial Pollution Intensity Index (B1): It reflects the pressure of pollutants discharged during industrial production in the assessment area on the ecological environment of the basin.

(2) Agricultural pollution intensity index (B2): It reflects the pressure of pollutants discharged/lost in the process of agricultural production in the assessment area on the ecological environment of the basin.

(3) Urban domestic pollution intensity index (B3): It reflects the pressure of pollutants discharged from urban domestic sewage in the assessment area on the ecological environment of the basin.

(4) Urban non-point source pollution intensity index (B4): It reflects the pressure on the ecological environment of the river basin caused by pollutants discharged from urban non-point sources in the assessment area.

The calculation formula of urban non-point source pollutant emissions is as follows:

G _total = ∑G _i ×10 ^-3

G _total - urban non-point source pollutant discharge, ton/year; G _i - annual pollutant amount of each underlying surface, kg/year, urban underlying surface is divided into roof, traffic road, green space and comprehensive land.

The calculation of the amount of pollutants on each underlying surface is shown in the following formula.

G _i =0.01αφPSEMC

In the formula: α—runoff correction coefficient; φ—runoff coefficient of drainage area; P—annual precipitation, mm/

year; S—area of each underlying surface, hectares; EMC—event average concentration, mg/L.

The specific descriptions of the above factors are as follows:

①The runoff correction coefficient α is generally 0.9;

② The runoff coefficient φ of the drainage area is generally the reference value in the literature, and the runoff coefficient of different underlying surfaces is different.

Table 1 Runoff coefficient value reference table

③ Annual precipitation P, which can be obtained from the data of meteorological or hydrological departments.

④The area S of the drainage area refers to the area of different underlying surfaces, that is, the area of the roof, traffic road, green space and comprehensive land, which can be obtained through interpretation of remote sensing data.

⑤ Event Mean Concentration EMC (Event Mean Concentration), refers to the flow-weighted average concentration of pollutants during a runoff pollution process, that is, the ratio of total pollutants to total runoff. In the absence of actual monitoring data, the Event Mean Concentration (EMC) in the table below can be used.

Table 2 Event Average Concentration (EMC) Reference Table Unit: mg/L

category COD TN TP Ammonia nitrogen roof 75.89 8.86 0.084 5.63 traffic pavement 197.45 7.91 0.28 5.19 green space 60.71 7 0.3 2.87 Comprehensive land 176.11 5.86 0.12 5.55

After the water environment index data of the basin is determined, the water environment carrying capacity data can be analyzed and processed more accurately, so as to realize the risk assessment. Specifically, the method includes:

Index normalization processing steps: In order to overcome the influence of different dimensions and magnitudes of evaluation indicators on the evaluation results, it is necessary to normalize the evaluation indicators. The positive index is processed by formula (1), the larger the value of the positive index, the greater the water environment carrying capacity; the reverse index is processed by formula (2), the larger the value of the reverse index, the smaller the water environment carrying capacity .

For positive indicators:

For contrarian indicators:

In the formula: V _j is the standardized index value, V _j ≤ 1; b _j is the actual value of the j-th index; B _jmax is the upper limit of the standard value of the interval corresponding to the actual value of the j-th index; B _jmin The j-th index The actual value corresponds to the lower limit of the standard value of the interval; Q _jmax is the upper limit of the bearing degree corresponding to the actual value of the jth index; _Qjmin is the lower limit of the bearing degree corresponding to the actual value of the jth index.

Weight determination step: Since various influencing factors of water environment carrying capacity are interconnected and restricted, there is great ambiguity and uncertainty. Therefore, it is necessary to select AHP to determine the weight of each indicator; this step specifically includes:

(1) Establish a hierarchical structure model

On the basis of in-depth analysis of practical problems, the relevant factors are decomposed into several levels from top to bottom according to different attributes. The top layer is the target layer, usually with only one factor, followed by the indicator layer.

(2) Constructing a pairwise comparison judgment matrix

An important feature of AHP is to express the corresponding importance level of the two indicators in the form of the ratio of the importance levels of each pair. The hierarchical structure model determines the affiliation between the elements of the upper and lower layers. For each element of the same layer, the elements in the adjacent upper layer are used as the criterion to compare them in pairs, and use the 1-9 scale scoring method (see Table 3) to delineate their relative importance or degree of pros and cons. If the judgment matrix B is denoted as (b _ij ) n×n, there are:

Table 3 Relative importance scale and significance

Scaling definition 1 two elements are of equal importance 3 Compared to two elements, one is slightly more important than the other 5 Comparing two elements, one is more important than the other 7 Compared with two elements, one is more important than the other 9 Comparing two elements, one is definitely more important than the other 2, 4, 6, 8 The median of the above two adjacent judgments 1/b_i,j Inverse comparison of two elements

(3) Determine the relative weight of each element by the judgment matrix

For the constructed judgment matrix, the eigenvector corresponding to the largest eigenvalue can be obtained, and the canonical column average method (sum product method) can be used for calculation.

The calculation steps are as follows:

Calculate normalization for each column

find the average of a canonical column

The vector W=(w ₁ ,w ₂ ,...,w _n ), where T is the desired eigenvector.

Calculate the largest eigenvalue of the judgment matrix B

where (BW) _i is the ith element in the vector BW.

The maximum eigenroot _λmax of each judgment matrix and its corresponding eigenvector W are obtained by using the sum-product method. The judgment matrix is checked for consistency according to the consistency ratio CR. If there is satisfactory consistency, the eigenvector W can be used as a single-ranked sorting weight vector after normalization. Otherwise, the scale of the judgment matrix needs to be properly corrected.

Whether the judgment matrix has satisfactory consistency is judged by the random consistency ratio CR. Generally, if CR<0.1, the judgment matrix is considered to have satisfactory consistency.

The formula for calculating CR is as follows:

In the formula: CR is the random consistency ratio; CI is the consistency index; RI is the average random consistency index, which can be found in Table 4; _λmax is the maximum eigenvalue of the judgment matrix; n is the order of the judgment matrix.

Table 4 Average random consistency index RI standard value

Evaluation model determination steps: use the weighted sum method to obtain a comprehensive index evaluation model S _WECC that characterizes the relative size of the regional water environment carrying capacity, namely:

In the formula, S _WECC is the comprehensive evaluation index of water environment carrying capacity; S _i is the score value of the ith index in the index layer; ω _i is the weight of the ith index in the index layer; m is the number of indexes.

Check the water environment carrying capacity according to the water pollutant concentration exceeding index

Calculate the regional water pollutant concentration exceeding index, which is reflected by the comparison between the annual average concentration monitoring value of major pollutants and the current national environmental quality standard.

According to the calculation results of the water pollutant concentration exceeding index, the necessary verification of the water environment carrying capacity S _WECC is carried out. When the pollutant concentration exceeding index is greater than 0, the water pollutant concentration is in a state of exceeding the standard, and the water environment carrying capacity S _WECC should be less than 0.5 in principle; when the pollutant concentration exceeding index is less than -0.2, the water pollutant concentration is not exceeding the standard. In principle, the water environment carrying capacity S _WECC should be greater than 0.75.

The calculation method of the water pollutant concentration exceeding index is as follows:

When i=1, that is, when the water pollutant is DO:

R _{water ijk} =1/(C _ijk /S _ik )-1

When i=2,...,6, that is, the water pollutants are COD _Mn , BOD ₅ , COD _Cr , NH ₃ -N, TP, respectively:

R _{water ijk} =C _ijk /S _ik -1

R _{water jk} =max(R _{water ijk} ), i=1,2,...,6

Among them, R _{water ijk} is the water pollutant concentration exceeding index of the k-th section in area j, R _{water ij} is the water pollutant concentration exceeding index of the i-th item in area j, and R _{water jk} is the water pollutant concentration of the k-th section of area j. Concentration exceeding index, R _{water j} is the concentration exceeding index of water pollutants in area j, C _ijk is the annual average concentration monitoring value of the i-th water pollutant in the k-th section of area j, S _ik is the i-th water pollutant in the k-th section Water quality standard limits for pollutants. i=1,2,...,6, corresponding to DO, COD _Mn , BOD ₅ , COD _Cr , NH ₃ -N, TP respectively; k is a certain control section, k=1,2,...,N _j ,N _j Indicates the number of control sections in area j.

When the pollutant concentration exceeding index is greater than 0, the water pollutant concentration is in an exceeding state; when the pollutant concentration exceeding index is between -0.2 and 0, the pollutant concentration is close to exceeding the standard; when the pollutant concentration exceeding index is less than -0.2 , the concentration of water pollutants is not exceeding the standard.

Table 5 Standard limits for basic items of surface water environmental quality standards (unit: mg/L)

Evaluation level division

The value range of the water environment carrying capacity (S _WECC ) is between 0 and 1, and its size reflects the quality of the regional water environment carrying capacity. The larger the value, the greater the water environment carrying capacity of the region; the value The smaller the value, the smaller the carrying capacity of the water environment in the area, the less it can bear the greater pressure, the weaker the water environment, and even on the verge of collapse.

In order to qualitatively evaluate the carrying capacity of the water environment, the value of the carrying capacity of the water environment is divided into different grades, so as to evaluate the magnitude of the carrying capacity of the water environment. The classification results are shown in Table 5.

Table 6 Classification of comprehensive evaluation grades of water environment carrying capacity

Water environment carrying capacity monitoring and early warning

According to the comprehensive evaluation results of the water environment carrying capacity, the early warning grades of the water environment carrying capacity are divided, as shown in Table 7.

Table 7 Classification of early warning levels of water environment carrying capacity

Suggest countermeasures

According to the evaluation results of the water environment carrying capacity, combined with the actual situation of the evaluation area, the main factors affecting the water environment carrying capacity of the area are analyzed from the perspectives of natural resource conditions, social and economic development, pollutant discharge and water environment management.

Starting from the two main lines of "capacity increase" and "emission reduction", the ecological water demand guarantee plan and the water pollutant reduction plan are proposed. Propose the construction plan for the monitoring and early warning mechanism of water environment carrying capacity, including the acquisition and transmission of basic data, the construction of the water environment carrying capacity research and judgment system, the analysis and release of carrying status, and the application of monitoring and early warning results, etc.

In this embodiment of the present invention, when processing water environment carrying capacity data, the following parameters may be further referenced: water resources index, water environment index, and water ecology index. specific:

1. Water Resources Index

(1) Development and utilization rate of water resources (A1): the ratio of water consumption (industry, agriculture, life, environment, etc.) to the average total water resources in the basin for many years.

(2) Water consumption per 10,000 yuan of GDP (A2): water consumption per unit of GDP (gross national product), that is, the ratio of total water consumption to gross national product (GDP).

(3) Water area per capita (A3): The water area per capita in the jurisdiction area, that is, the ratio of the total population to the total water area. This indicator mainly reflects the water resources endowment of human beings, and also responds to the characteristics of water ecology and water environment.

2. Water Environment Index

(1) Industrial Pollution Intensity Index (B1): It reflects the pressure of pollutants discharged during the industrial production process in the assessment area on the ecological environment of the basin.

(2) Agricultural pollution intensity index (B2): It reflects the pressure of pollutants discharged/lost in the process of agricultural production in the assessment area on the ecological environment of the basin.

(3) Urban domestic pollution intensity index (B3): It reflects the pressure of pollutants discharged from urban domestic sewage in the assessment area on the ecological environment of the basin.

(4) Urban non-point source pollution intensity index (B4): It reflects the pressure on the ecological environment of the river basin caused by the pollutants discharged from urban non-point sources in the assessment area.

The calculation formula of urban non-point source pollutant emissions is as follows:

G _total = ∑G _i ×10 ^-3

G _total - urban non-point source pollutant discharge, ton/year; G _i - annual pollutant amount of each underlying surface, kg/year, urban underlying surface is divided into roof, traffic road, green space and comprehensive land.

The calculation of the amount of pollutants on each underlying surface is shown in the following formula.

G _i =0.01αφPSEMC

In the formula: α—runoff correction coefficient; φ—runoff coefficient of drainage area; P—annual precipitation, mm/

year; S—area of each underlying surface, hectares; EMC—event average concentration, mg/L.

The specific descriptions of the above factors are as follows:

①The runoff correction coefficient α is generally 0.9;

② The runoff coefficient φ of the drainage area is generally the reference value in the literature, and the runoff coefficient of different underlying surfaces is different.

Runoff coefficient value reference table

category reference value roof 0.90 traffic pavement 0.80 green space 0.20 Comprehensive land 0.60

③ Annual precipitation P, which can be obtained from the data of meteorological or hydrological departments.

④The area S of the drainage area refers to the area of different underlying surfaces, that is, the area of the roof, traffic road, green space and comprehensive land, which can be obtained through interpretation of remote sensing data.

⑤ Event Mean Concentration EMC (Event Mean Concentration), refers to the flow-weighted average concentration of pollutants during a runoff pollution process, that is, the ratio of total pollutants to total runoff. In the absence of actual monitoring data, the Event Mean Concentration (EMC) in the table below can be used.

The average event concentration (EMC) can refer to the table unit: mg/L

category COD TN TP Ammonia nitrogen roof 75.89 8.86 0.084 5.63 traffic pavement 197.45 7.91 0.28 5.19 green space 60.71 7 0.3 2.87 Comprehensive land 176.11 5.86 0.12 5.55

Water ecological data:

(1) Vegetation-covered shoreline ratio (C1): the proportion of river vegetation-covered (>3m) shoreline to the total shoreline. It reflects the impact of the vegetation coverage on the river bank on the river ecology. The larger the proportion of vegetation coverage on the shoreline, the better the river ecological status, and vice versa.

(2) River natural shoreline ratio (C2): the proportion of river natural shoreline to the total shoreline, the more natural shorelines, the more suitable for biological growth and the better the river habitat condition.

(3) River connectivity (C3): The number of hydropower station gates and dams built per unit length of the river. It reflects that the fewer gates and dams in the hydropower station, the better the longitudinal connectivity of the river, the better the spatial connectivity of nutrient flow and energy flow, the better the spatial connectivity of biological community structure and the spatial connectivity of information flow, and the greater the carrying capacity of the water environment.

(4) Guaranteed rate of ecological base flow (C4): The percentage of the actual flow in the base year and month to the minimum ecological base flow.

The minimum ecological base flow in the formula:

W _Eb = annual average flow in the past 10 years × 10%

For those without hydrological station data, the minimum ecological base flow of the river can be calculated by referring to the relevant parameters in the table below.

Habitat conditions of the lower water system at different time periods

Calculation period division Ecological water depth (m) Ecological velocity (m/s) T1 period (March 1 to May 31) 0.6 0.02 T2 period (June 1st to August 31st) 0.8 0.05 T3 period (September 1st to October 31st) 0.8 0.02 T4 period (November 1st to February 28th of the following year) - -

The above solution of the present invention proposes a water environment index data processing method. By establishing a water environment index data set, an accurate data processing method can be provided for the water environment index, so as to more accurately evaluate the water environment carrying capacity, Prevent human society from causing irreversible damage to the natural environment.

The above are the preferred embodiments of the present invention. It should be pointed out that for those skilled in the art, without departing from the principles of the present invention, several improvements and modifications can be made. It should be regarded as the protection scope of the present invention.

Claims (7)

1. a water environment index data processing method, is characterized in that, comprises: Determine the industrial pollution intensity index, agricultural pollution intensity index, urban domestic pollution intensity index, and urban non-point source pollution intensity index of the target water area; Generate a water environment index dataset. 2. The water environment index data processing method according to claim 1, wherein the determining the industrial pollution intensity index comprises: The industrial pollution intensity index B1 is determined by the pollutants emitted by the industry:

3. The water environment index data processing method according to claim 1, wherein the determining the agricultural pollution intensity index comprises: The agricultural pollution intensity index B2 is determined by the pollutants emitted by agriculture:

4. The water environment index data processing method according to claim 1, wherein the determining the urban non-point source pollution intensity index comprises: Through the pollutants discharged by urban life, determine the urban life pollution intensity index B3:

5. The water environment index data processing method according to claim 1, wherein the determining the urban domestic pollution intensity index comprises: Through the pollutants discharged from urban non-point sources, determine the urban domestic pollution intensity index B4:

6. The water environment index data processing method according to claim 4, wherein the determining the urban domestic pollution intensity index comprises: The calculation formula of urban non-point source pollutant emissions is as follows: G _total = ∑G _i ×10 ^-3 G _total - urban non-point source pollutant discharge, ton/year; G _i - annual pollutant amount of each underlying surface, kg/year, urban underlying surface is divided into roof, traffic road, green space and comprehensive land. 7. water environment index data processing method according to claim 5, is characterized in that, the pollutant amount of each underlying surface is calculated by following formula: G _i =0.01αφPSEMC where: α—runoff correction coefficient; φ—runoff coefficient of drainage area; P—annual precipitation, mm/year; S—area of each underlying surface, hectare; EMC—event average concentration, mg/L.

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