CN110942206B - Method for predicting position of water supply boundary zone of pipe network - Google Patents

Method for predicting position of water supply boundary zone of pipe network Download PDF

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CN110942206B
CN110942206B CN201911233324.9A CN201911233324A CN110942206B CN 110942206 B CN110942206 B CN 110942206B CN 201911233324 A CN201911233324 A CN 201911233324A CN 110942206 B CN110942206 B CN 110942206B
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pipe network
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quality index
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CN110942206A (en
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杨玉龙
汤晗青
庞志成
张土乔
张可佳
费伟成
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Zhejiang University ZJU
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Abstract

The invention discloses a characteristic water quality index space correction interpolation method for predicting a position of a water supply boundary zone of a pipe network. The method mainly selects an index with larger difference of the leaving water and regular distribution in a pipe network as a characteristic water quality index, corrects the characteristic index according to the difference of the pipe network distribution and the geographic space, and performs spatial interpolation to obtain the spatial distribution condition of the corrected characteristic index; and predicting the position of the water supply boundary zone according to the numerical range of the characteristic index of the mixed water of the boundary zone. The method for predicting the position of the water supply boundary zone can provide a basis for arranging a new boundary zone water quality risk monitoring point after a water supply network is newly built, reconstructed and expanded.

Description

Method for predicting position of water supply boundary zone of pipe network
Technical Field
The invention relates to the field of water quality monitoring of domestic drinking water, in particular to a characteristic water quality index space correction interpolation method for predicting the position of a water supply boundary zone of a pipe network.
Background
With the acceleration of the urbanization process, the water supply pattern of multiple water sources is increasing day by day, and the water quality risk points of the pipe network are often distributed in the water supply boundary zone, the aging pipeline and the pipe network tip. Wherein, the water supply boundary zone is the junction of the factory waters with different water qualities, which is easy to cause nutrition complementation and biochemical reaction, resulting in residual chlorine loss. The water pressure in the area is unstable, the water flow direction and the water flow speed are frequently changed, the deposits on the pipe wall and the biological membrane are easily washed, the turbidity is increased, and the iron release is accelerated. In addition, the original hydraulic conditions can be changed by changing the water supply amount, adjusting the water pressure and the like, so that the water supply boundary zone fluctuates or deviates obviously, the water body flowing through the nearby pipeline changes suddenly, and the risk of 'yellow water' is increased. The boundary zone position is accurately predicted, and the local water quality problem can be more pertinently monitored and improved.
The water supply boundary zone can be generally predicted by a hydraulic model, and the water quality detection is also assisted in partial research to correct the prediction result. The establishment of the hydraulic model requires a large amount of pipe network data, the process is complex, and the time consumption is long. Due to the difference of water sources, treatment processes and the like, water quality indexes with large difference, such as conductivity, residual chlorine, inorganic salt content and the like, may exist in factory water of different water plants, are distributed in a pipe network according to a certain rule, have obvious identification characteristics, and can be used as characteristic indexes to judge the position of a water supply boundary zone. Discrete measurement data such as sampling point water quality indexes can be converted into a continuous data curved surface by adopting a space interpolation method. The method comprises two algorithms of spatial interpolation and extrapolation, has wide application field, and has related application in forest resources, air temperature, GDP, water supply pressure, soil elements and the like. However, unlike the general geographical plane, it is not suitable to directly interpolate and study the pipe network water flowing according to the geographical space.
Therefore, the method is different from a common hydraulic model method, and predicts the water supply boundary zone by adopting a spatial interpolation method based on the characteristic water quality index. In the interpolation process, the characteristic indexes are corrected firstly in consideration of the fact that the numerical distribution of the water quality indexes is not only related to the geographic space, but also related to the distribution of a pipe network system.
Disclosure of Invention
The invention provides a characteristic water quality index spatial correction interpolation method for predicting the position of a water supply boundary zone of a pipe network, which mainly selects water quality indexes with obvious identification characteristics as characteristic indexes by selecting the large difference and the distribution rule of factory water of different water plants, corrects the characteristic indexes according to the pipe network distribution and the geographical spatial difference and performs spatial interpolation to obtain the spatial distribution condition of the corrected characteristic indexes; and finally, predicting the position of the water supply boundary zone according to the characteristic index numerical range of the mixed water in the boundary zone.
A characteristic water quality index space correction interpolation method for predicting a position of a water supply boundary zone of a pipe network comprises the following steps:
(1) detecting the water quality indexes of the water leaving the water works, calculating the ratio of the detected water quality indexes of the water leaving the water works, and selecting the ratio to be more than 2 or less than
Figure BDA0002304179330000021
The water quality index of (2) as a characteristic water quality index;
(2) mixing the outgoing water of the two water plants according to a proportion, detecting characteristic water quality indexes under different mixing proportions to obtain different characteristic water quality index numerical values, wherein different characteristic water quality index numerical ranges are the mixing numerical range for judging the water supply boundary zone;
(3) setting each sampling point on the pipe network between two water plants, detecting the characteristic index value of the pipe network water (tap water) of each sampling point as the sample point pipe network water quality index measured value zi；
(4) According to the difference between the pipe network distribution and the geographic space, the water quality index measured value z of the sampling point pipe network obtained in the step (3)iCorrecting;
(5) sample point pipe network water quality index correction value zi' performing a spatial interpolation analysis;
(6) and (4) judging the position of the water supply boundary zone according to the spatial interpolation analysis result obtained in the step (5) and the blending numerical range of the water supply boundary zone judged in the step (2).
In the step (1), the water quality indexes comprise conductivity, hardness, turbidity, total iron concentration and residual chlorine. The detected water quality indexes comprise conductivity, hardness, turbidity, total iron concentration and residual chlorine, and the spatial distribution in the pipe network has a rule. Wherein the conductivity, the hardness, the turbidity and the total iron concentration are obviously increased along with the increase of the flowing distance of the water body; the concentration of the residual chlorine is obviously decreased along with the increase of the flowing distance of the water body. The conductivity is measured by a conductivity meter; measuring the hardness by using a hardness detector; measuring the turbidity by a turbidity meter; the total iron concentration is measured by ICPMS; residual chlorine is measured by a residual chlorine meter.
The ratio of the characteristic water quality index of the factory water of the two water plants is more than 2 or less than
Figure BDA0002304179330000022
The numerical value difference is large, interpolation distribution areas in a pipe network can be distinguished, and characteristic water quality indexes of a water supply boundary zone can be selected. For example, the ratio of the water quality index conductivity of the water from the two water plants is more than 2 or less
Figure BDA0002304179330000023
Then the conductivity is used as the characteristic water quality indexFor example, the ratio of the water quality index conductivity of the water from the two water plants is more than 2 or less
Figure BDA0002304179330000031
The ratio of the water quality index hardness of the water leaving the two water plants is also more than 2 or less than
Figure BDA0002304179330000032
Both the conductivity and the hardness are taken as characteristic water quality indexes.
In the step (2), the outgoing water of the two water plants is mixed according to a proportion, the characteristic water quality indexes under different mixing proportions are detected, different characteristic water quality index values are obtained, and different characteristic water quality index value ranges are the blending value range for judging the water supply boundary zone, and the method specifically comprises the following steps:
mixing the factory water of two water plants uniformly according to the volume ratio of 4:6, 5:5 and 6:4 respectively, and detecting the corresponding characteristic water quality index value X4:6、X5:5、X4:6Obtaining the blending numerical range for judging the water supply boundary zone, wherein the minimum value of the range is X4:6、X5:5、X4:6Of which the maximum value is X4:6、 X5:5、X4:6Maximum value of (2).
Mixed value range X for judging water supply boundary zone4:6～X6:6(or X)6:4～X4:6) The areas where the water of different water plants is uniformly mixed and has close proportion, namely the area where the water of one water plant accounts for 40-60 percent and the water of the corresponding other water plant accounts for 60-40 percent, are water supply boundary zones. The numerical range X4:6～X6:6(or X)6:4～X4:6) The water supply boundary zone position in the spatial interpolation distribution map is judged.
The water in different water plants is uniformly mixed, and the areas with close proportion (the proportion is 4:6, 5:5 and 6:4) are water supply boundary zones. The numerical range X4:6～X6:6(or X)6:4～X4:6) The water supply boundary zone position in the spatial interpolation distribution map is judged. X5:5The value of (A) is in X4:6And X6:4In the meantime.
In the step (3), each sampling point is arranged on the pipe network between the two water plants, and the method specifically comprises the following steps:
selecting sampling points uniformly distributed on the pipe network every 1-4 km (most preferably 2km) by taking two water plant positions as starting points, detecting the characteristic index numerical value of the pipe network water (tap water) of each sampling point as a sample point pipe network water quality index actual measurement value zi。
Sampling points are uniformly distributed in the area between the two water plants at intervals of 2km, and in order to enable the predicted position of the boundary zone to be more accurate, the sampling points can be encrypted at intervals of 1km on a connecting line of the two water plants and a pipe network which passes through the middle point of the connecting line of the two water plants and is perpendicular to the connecting line of the two water plants.
In the step (4), according to the difference between the distribution of the pipe network and the geographic space, the water quality index measured value z of the sampling point pipe network obtained in the step (3) is measurediThe correction specifically comprises:
according to the formula
Figure BDA0002304179330000033
Correcting the characteristic water quality index;
wherein z is0Is the measured value of the water quality index of the factory water; z is a radical ofiIs a sample point pipe network water quality index measured value; z is a radical ofi' is a sample point pipe network water quality index correction value; diIs the geographical linear distance between the water plant and the sampling point; siIs the distance of the pipeline through which water flows from the water plant to the sampling point;
the characteristic water quality index is corrected according to the difference between the distribution of the pipe network and the geographic space, and because water flows in the pipe network, the numerical distribution of the water quality index is not only related to the geographic space, but also related to the distribution of the pipe network, so that the characteristic index is corrected according to the difference between the distribution of the pipe network and the geographic space, and then interpolation prediction is carried out.
Correction formula
Figure BDA0002304179330000041
In z0Is the measured value of the water quality index of the factory water; z is a radical ofiIs a water quality index measured value of a pipe network sampling point; z'iIs a water quality index correction value of a pipe network sampling point; diIs the geographical linear distance between the water plant and the sampling point; siIs the distance through the pipeline from the water plant to the sampling point. diMeasured directly from map measurements; siThe method is obtained through the statistics of the existing GIS system. For different spots, diAnd siThe ratio of (a) to (b) is different. Due to the fact that
Figure BDA0002304179330000042
After correction, z'i<zi。
In the step (5), ArcGIS software is used for correcting the sampling point pipe network water quality index correction value z'iAnd carrying out spatial interpolation analysis.
The ArcGIS software spatial interpolation analysis can convert discrete measurement data such as sampling point water quality indexes and the like into a continuous data curved surface by a Krigin interpolation method to obtain a continuously-changed characteristic water quality index spatial distribution band.
The corrected values of the conductivity and the hardness can be directly interpolated by ArcGIS software to obtain a distribution result. Turbidity, total iron concentration, residual chlorine concentration, and chemical and biological reactions in the boundary zone, wherein the number of the sample points is 2 times or more of that of the peripheral sample points (sample points 2km away), or
Figure BDA0002304179330000043
The following discontinuities are removed prior to interpolation. Because the water quality index changes continuously in the pipe network, if the value appears, the value is especially large (more than 2 times of the value of the peripheral sampling point) or especially small (the value of the peripheral sampling point)
Figure BDA0002304179330000044
Following) points, whether there is a measurement error (error) or biochemical adverse change needs to be considered, and in any case, such points should be removed before interpolation processing, and then interpolation analysis is performed on other data.
In the step (6), the position of the water supply boundary zone is judged according to the spatial interpolation analysis result obtained in the step (5) and the blending numerical range of the water supply boundary zone judgment obtained in the step (2), and the method specifically comprises the following steps:
and (5) obtaining a spatial interpolation analysis result, namely obtaining a change graph of the corrected characteristic water quality indexes of the region between the two water plants according to the strip distribution and the numerical value range of each zone, and finding a corresponding numerical value zone on the graph, namely the predicted position of the water supply boundary zone according to the blending numerical value range of the water supply boundary zone judged in the step (2).
The ArcGIS interpolation analysis result can obtain the change chart of the area between two water plants and the characteristic water quality index distributed according to the strip and the numerical range of each strip. According to X4:6～X6:6(or X)6:4～X4:6) And finding a corresponding numerical value band on the graph, namely the predicted water supply boundary band position.
Compared with the prior art, the invention has the following advantages:
the invention discloses a characteristic water quality index space correction interpolation method for predicting a water supply boundary zone of a pipe network. The method mainly selects an index with larger difference of the leaving water and regular distribution in a pipe network as a characteristic water quality index, corrects the characteristic index according to the difference of the pipe network distribution and the geographic space, and performs spatial interpolation to obtain the spatial distribution condition of the corrected characteristic index; and predicting the position of the water supply boundary zone according to the numerical range of the characteristic index of the mixed water of the boundary zone. The method is a practical method for predicting the position of the water supply boundary zone of the pipe network, and the method for rapidly predicting the position of the water supply boundary zone only needs water quality detection and data processing is tried to be adopted in consideration of the complexity of a hydraulic model prediction method. The method can provide a basis for arranging a new water supply boundary zone water quality risk monitoring point after a water supply pipe network is newly built, reconstructed and expanded and other related researches.
Drawings
FIG. 1 is a schematic flow chart of a characteristic water quality index space correction interpolation method for predicting a water supply boundary zone position of a pipe network according to the present invention;
FIG. 2 is a graph of H market sample point distribution;
FIG. 3 is a diagram illustrating water supply boundary zone prediction before H commercial power conductivity correction;
FIG. 4 is a diagram of water supply boundary zone prediction after the commercial power conductivity is corrected;
FIG. 5 is a water supply boundary zone prediction comparison graph before and after the H mains electricity conductivity correction, and the dotted line of the overlapping part is the right boundary of the prediction result before the correction;
FIG. 6 is a water supply boundary zone prediction graph (without removing sensitive points) after the total iron concentration in H city is corrected;
FIG. 7 is a water supply boundary band prediction chart (sensitive point removal) after the total iron concentration in H city is corrected.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
As shown in fig. 1, a characteristic water quality index space correction interpolation method for predicting a water supply boundary zone position of a pipe network includes the following steps:
(1) detecting water quality indexes of the water leaving the water plants, wherein the water quality indexes comprise conductivity, hardness, turbidity, total iron concentration and residual chlorine, and the conductivity, hardness, turbidity and total iron concentration are obviously increased along with the increase of the flowing distance of the water body; the concentration of the residual chlorine is obviously decreased along with the increase of the flowing distance of the water body. The conductivity is measured by a conductivity meter; measuring the hardness by using a hardness detector; measuring the turbidity by a turbidity meter; the total iron concentration is measured by ICPMS; measuring residual chlorine by a residual chlorine meter, calculating the ratio of the quality indexes of the two detected water works leaving the factory, and selecting the ratio to be more than 2 or less than
Figure BDA0002304179330000051
The water quality index of (2) as a characteristic water quality index;
(2) mixing the factory water of two water plants uniformly according to the volume ratio of 4:6, 5:5 and 6:4 respectively, and detecting the corresponding characteristic water quality index value X4:6、X5:5、X4:6Obtaining the blending numerical range for judging the water supply boundary zone, wherein the minimum value of the range is X4:6、X5:5、X4:6Of which the maximum value is X4:6、X5:5、X4:6Maximum value of (1);
(3) selecting sampling points are uniformly distributed on the pipe network every 2km by taking the positions of two water plants as starting points, and in order to ensure that the predicted position of the boundary zone is more accurate, the sampling points can be connected between the two water plants and connected between the two water plantsThe characteristic index value of the pipe network water (tap water) of each sampling point is detected as the actual measurement value z of the pipe network water quality index of the sampling point on a pipe network vertical to the connecting line of two water plants at intervals of 1km encrypted sampling pointsi。
(4) According to the difference between the pipe network distribution and the geographic space, the water quality index measured value z of the sampling point pipe network obtained in the step (3)iCorrecting;
according to the formula
Figure BDA0002304179330000061
Correcting the characteristic water quality index;
wherein z is0Is the measured value of the water quality index of the factory water; z is a radical ofiIs a sample point pipe network water quality index measured value; z'iIs a sample point pipe network water quality index correction value; diIs the geographical linear distance between the water plant and the sampling point; siIs the distance of the pipeline through which the water flows from the water plant to the sampling point, diMeasured directly from map measurements; siThe method is obtained through the statistics of the existing GIS system. For different spots, diAnd siThe ratio of (a) to (b) is different. Due to the fact that
Figure BDA0002304179330000062
After correction, z'i<zi。
(5) Sample point pipe network water quality index correction value z'iCarrying out spatial interpolation analysis;
ArcGIS software space interpolation analysis can convert discrete measurement data such as sampling point water quality indexes and the like into a continuous data curved surface by a Krigin interpolation method to obtain a continuously-changed characteristic water quality index space distribution band. The corrected values of the conductivity and the hardness can be directly interpolated by ArcGIS software to obtain a distribution result. Turbidity, total iron concentration, residual chlorine concentration, and chemical and biological reactions in the boundary zone, wherein the number of the sample points is 2 times or more of that of the peripheral sample points (sample points 2km away), or
Figure BDA0002304179330000063
The following mutation points are first processed before interpolationSuch mutation points are removed. Because the water quality index changes continuously in the pipe network, if the value appears, the value is especially large (more than 2 times of the value of the peripheral sampling point) or especially small (the value of the peripheral sampling point)
Figure BDA0002304179330000064
Following) points, whether there is a measurement error (error) or biochemical adverse change needs to be considered, and in any case, such points should be removed before interpolation processing, and then interpolation analysis is performed on other data.
(6) And (5) obtaining a spatial interpolation analysis result, namely obtaining a change graph of the corrected characteristic water quality indexes of the region between the two water plants according to the strip distribution and the numerical value range of each zone, and finding a corresponding numerical value zone on the graph, namely the predicted position of the water supply boundary zone according to the blending numerical value range of the water supply boundary zone judged in the step (2).
Example 1
Taking the H market of the water supply of the double water plants as an example, the difference of the conductivity of the two water plants is large (the conductivity of the T water plant is 190 percent larger than that of the C water plant, namely the ratio of the conductivity of the T water plant to that of the C water plant is 2.9). The sampling points are shown in figure 2. Mixing the water from the C water plant and the water from the T water plant according to the ratio of 4:6, 5:5 and 6:4, and determining that the conductivity of the boundary belt is within the range of 200-250 us/cm.
According to a correction formula
Figure BDA0002304179330000071
The conductivity was corrected and the results are shown in table 1 below.
Table 1 conductivity correction table (part)
Numbering Measured value Correction value Numbering Measured value Correction value Numbering Measured value Correction value
1 136.3 131.1 9 351 338.7 17 407 373.3
2 282 253.4 10 350 336.4 18 409 382.8
3 144 140.9 11 322 321 19 384 373.2
4 137.3 132.7 12 381 356.6 20 375 363.2
5 130.6 127.2 13 384 368.7 21 386 373.5
6 137.1 136.9 14 388 372.3 22 382 361.3
7 197.9 168.6 15 360 348 23 396 373.2
8 202.2 186.9 16 365 356.7 24 110.1 110.1
After the conductivity correction, interpolation analysis can be directly carried out by a kriging method, and the zones shown in the figures 3 and 4 are the zones of the boundary zone of the space interpolation prediction before and after the conductivity correction. Comparing fig. 3 and fig. 4, it is found that the conductivity distribution and the change rule before and after the correction are similar. The two simulation results are loaded into a graph, as shown in fig. 5, and the dotted line of the overlapped part is the right boundary of the prediction result before correction. The simulation result after correction is shifted to the east as a whole than before correction.
And comparing the conductivity spatial interpolation prediction result before and after correction with the actual boundary zone, wherein the corrected interpolation prediction result is closer to the actual condition and is basically consistent with the actual condition.
Example 2 differs from example 1 only in that the characteristic indicator interpolated is the total iron concentration.
FIG. 6 shows the spatial interpolation results of total iron concentration without removing the mutation point in the demarcation zone, the interpolation zone is disordered, and there is no mixed zone (the range obtained by the total iron concentration mixing experiment) with the value of 0.10-0.12 mg/L. When the data of the sample points is observed, the value of 0.42mg/L in the virtual coil is far larger than the values of other sample points and is about 3-4 times of the total iron concentration (0.08mg/L and 0.15mg/L) of the sample points nearby. This value is likely to be the sensitive spot caused by the release of demarcation strip iron, and after removal of this spot, interpolation results are recovered, as shown in figure 7. Through comparison, the prediction result is basically consistent with the interpolation prediction result after the conductivity correction; the removed point is at the edge of a predicted boundary zone, and the abnormal condition of iron release at the point needs to be concerned.

Claims (4)

1. A characteristic water quality index space correction interpolation method for predicting a position of a water supply boundary zone of a pipe network is characterized by comprising the following steps:
(1) detecting the water quality indexes of the water leaving the water works, calculating the ratio of the detected water quality indexes of the water leaving the water works, and selecting the ratio to be more than 2 or less than
Figure DEST_PATH_IMAGE002
The water quality index of (2) as a characteristic water quality index;
the water quality indexes comprise conductivity, hardness, turbidity, total iron concentration and residual chlorine;
(2) mixing the outgoing water of the two water plants according to a proportion, detecting characteristic water quality indexes under different mixing proportions to obtain different characteristic water quality index numerical values, wherein different characteristic water quality index numerical ranges are the mixing numerical range for judging the water supply boundary zone;
(3) setting each sampling point on the pipe network between two water plants, detecting the characteristic index value of the pipe network water of each sampling point as the water quality index actual measurement value of the pipe network water of the sampling point
Figure DEST_PATH_IMAGE004
；
(4) According to the difference between the pipe network distribution and the geographic space, the water quality index actual measurement value of the sampling point pipe network obtained in the step (3)
Figure 574688DEST_PATH_IMAGE004
The correction specifically comprises:
according to the formula
Figure DEST_PATH_IMAGE006
Correcting the characteristic water quality index;
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE008
is the measured value of the water quality index of the factory water;
Figure 378914DEST_PATH_IMAGE004
is a sample point pipe network water quality index measured value;
Figure DEST_PATH_IMAGE010
is a sample point pipe network water quality index correction value;
Figure DEST_PATH_IMAGE012
is the geographical linear distance between the water plant and the sampling point;
Figure DEST_PATH_IMAGE014
is the distance of the pipeline through which water flows from the water plant to the sampling point;
(5) correction value of water quality index of sampling point pipe network
Figure 34017DEST_PATH_IMAGE010
Carrying out spatial interpolation analysis;
(6) and (3) judging the position of the water supply boundary zone according to the spatial interpolation analysis result obtained in the step (5) and the blending numerical range of the water supply boundary zone judgment obtained in the step (2), and specifically comprising the following steps:
and (5) obtaining a spatial interpolation analysis result, namely obtaining a change graph of the corrected characteristic water quality indexes of the region between the two water plants according to the strip distribution and the numerical value range of each zone, and finding a corresponding numerical value zone on the graph, namely the predicted position of the water supply boundary zone according to the blending numerical value range of the water supply boundary zone judged in the step (2).
2. The method for predicting the characteristic water quality index space correction interpolation of the position of the water supply boundary zone of the pipe network according to claim 1, wherein in the step (2), the leaving water of two water plants is mixed according to a proportion, the characteristic water quality indexes under different mixing proportions are detected, different characteristic water quality index values are obtained, different characteristic water quality index value ranges are the mixing value ranges for judging the water supply boundary zone, and the method specifically comprises the following steps:
mixing the factory water of two water plants uniformly according to the volume ratio of 4:6, 5:5 and 6:4 respectively, and detecting the corresponding characteristic water quality index value X4:6、X5:5、X6:4Obtaining the blending numerical range for judging the water supply boundary zone, wherein the minimum value of the range is X4:6、X5:5、X6:4Of which the maximum value is X4:6、X5:5、X6:4Maximum value of (2).
3. The method for predicting the characteristic water quality index space correction interpolation of the position of the water supply boundary zone of the pipe network according to claim 1, wherein in the step (3), each sampling point is arranged on the pipe network between two water plants, and the method specifically comprises the following steps:
selecting sampling points uniformly distributed on a pipe network every 1-4 km by taking two water plant positions as starting points, detecting the characteristic index numerical value of the pipe network water of each sampling point as a sample point pipe network water quality index actual measurement value
Figure 22702DEST_PATH_IMAGE004
。
4. The method for spatial correction and interpolation of characteristic water quality indexes for predicting the position of a water supply boundary zone of a pipe network according to claim 1, wherein in the step (5), a kriging interpolation method is used for correcting the correction value of the water quality indexes of the pipe network at the sampling point
Figure 305915DEST_PATH_IMAGE010
And carrying out spatial interpolation analysis.
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CN107610021B (en) * 2017-07-21 2021-02-09 华中农业大学 Comprehensive analysis method for space-time distribution of environment variables
CN110441488B (en) * 2019-07-01 2020-07-07 生态环境部卫星环境应用中心 Method and device for judging water quality of ocean ecological red line to reach standard

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