Underground water dynamic monitoring well pattern optimization method based on fouling and risk partition

Abstract

The invention discloses a groundwater dynamic monitoring well pattern optimization method based on fouling and risk partitions. The method comprises the following steps: determining a hydrogeological background and groundwater function partitions of a to-be-optimized region; analyzing the fouling property according to the hydrogeological background, and obtaining a fouling property grade; obtaining a groundwater protection urgency level according to the fouling level and the groundwater function partition; determining an existing monitoring well in a to-be-optimized area and sampling, and analyzing the water quality principal component to obtain the water quality principal component of underground water in the to-be-optimized area; the underground water pollution degree is obtained; according to the groundwater pollution degree and the groundwater protection urgency level, obtaining a groundwater pollution risk level; and according to the groundwater pollution risk level, dynamically monitoring the to-be-optimized area, and optimizing the monitoring well pattern. According to the invention, dynamic adjustment and optimization are carried out according to the pollution degree of the underground water, so that the new underground water dynamic monitoring well pattern can obtain enough amount of underground water information data with higher precision under the precondition of using less manpower and material resources.

Description

Technical Field

[0001] The present invention relates to the technical field of groundwater monitoring, and in particular to a groundwater dynamic monitoring well network optimization method based on pollution susceptibility and risk zoning. Background Art

[0002] Groundwater is a valuable natural resource and an important environmental factor closely related to human survival. The purpose of establishing a groundwater monitoring well network and conducting groundwater dynamic monitoring is to further identify and study hydrogeological conditions, especially groundwater recharge, runoff, and discharge conditions, to understand the dynamic laws of groundwater, and to provide a scientific basis for groundwater resource evaluation, scientific management, and the research and prevention of environmental geological problems.

[0003] With the continuous progress of science and technology, the shortcomings of the original groundwater monitoring well network are becoming increasingly obvious. For example, in the absence of an evaluation of the rationality, effectiveness and reliability of the monitoring well network system, people are eager to invest in construction. In addition, the density of the well network is also unreasonable. In some areas, the density is too small, the point setting is poor, and the observation frequency is too low, which causes the monitoring network system to be unable to provide sufficient, reasonable, effective and reliable data information; in some areas, the well network density is too large, the observation frequency is high, and a lot of manpower and material resources are consumed, resulting in a waste of funds. This is because in the process of establishing and managing the monitoring network, the scientific rationality and integrity of the groundwater monitoring well network setting, as well as the comprehensive evaluation of the effectiveness and reliability of the various data information provided, have been ignored.

[0004] Carrying out groundwater dynamic monitoring is an important basic work for groundwater resource evaluation planning, rational development and utilization, and optimal allocation and scheduling, and is an important part of groundwater resource management. Groundwater includes two aspects: water quantity and water quality. The changes in groundwater quantity, water quality, and physical properties over time are called groundwater dynamics. Studying groundwater dynamics is one of the most effective ways to understand the formation and properties of groundwater resources. Groundwater dynamic prediction is an important intermediate link between correctly understanding local hydrogeological conditions (including understanding and quantitative evaluation of the properties of groundwater resources) and rational development and utilization of groundwater.

[0005] Therefore, the problems existing in the prior art need to be further improved and developed. Summary of the invention

[0006] (I) Purpose of the invention: In order to solve the problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a method for optimizing the groundwater dynamic monitoring well network based on contamination susceptibility and risk zoning.

[0007] (II) Technical solution: In order to solve the above technical problems, this technical solution provides a groundwater dynamic monitoring well network optimization method based on pollution susceptibility and risk zoning, which specifically includes: Step 1, determining the hydrogeological background and groundwater functional zoning of the area to be optimized;

[0008] Step 2: Analyze the pollution susceptibility of the area to be optimized according to the hydrogeological background, and obtain the pollution susceptibility level; and obtain the groundwater protection urgency level according to the pollution susceptibility level and groundwater functional zoning;

[0009] Step 3, determine the existing monitoring wells in the area to be optimized and take samples from them, analyze the principal components of the water quality of the groundwater in the area to be optimized, and obtain the principal components of the water quality of the groundwater in the area to be optimized; thereby obtaining the degree of groundwater pollution in the area to be optimized;

[0010] Step 4: Obtain the groundwater pollution risk level according to the groundwater pollution degree and groundwater protection urgency level of the area to be optimized;

[0011] Step 5: According to the groundwater pollution risk level, dynamically monitor the optimized area and optimize the monitoring well network.

[0012] Preferably, a basic status survey is conducted on the area to be optimized to understand the hydrogeological background and groundwater functional zoning of the area to be optimized.

[0013] Preferably, the step 2 specifically includes:

[0014] Step 201, using the DRASTIC evaluation method to analyze the groundwater pollution susceptibility of the area to be optimized, and quantifying the pollution susceptibility level;

[0015] Step 202: Obtain the groundwater protection urgency level according to the pollution susceptibility level and groundwater functional zoning.

[0016] Preferably, the DRASTIC evaluation method is subdivided into different value ranges or media types, and an index value is used to quantify the influence of the value range and / or the media type on the groundwater contamination susceptibility to obtain a groundwater contamination susceptibility index;

[0017] The groundwater pollution susceptibility index is arranged from small to large, and the groundwater pollution susceptibility is divided into five levels: low groundwater pollution susceptibility, low groundwater pollution susceptibility, medium groundwater pollution susceptibility, high groundwater pollution susceptibility, and high groundwater pollution susceptibility.

[0018] Preferably, the pollution susceptibility level of the optimized area is assigned 1-5 points from low to high, and the groundwater functional zoning of the optimized area is assigned 1-5 points from low to high in importance;

[0019] According to the pollution susceptibility level and groundwater functional zoning of the area to be optimized, the scores of the two are added together to obtain the groundwater protection urgency level reflecting the severity of the pollution consequences; the groundwater protection urgency level is divided into five levels from low to high, namely low, lower, medium, higher, and high.

[0020] Preferably, the step 3 specifically includes:

[0021] Step 301: locate and sample the monitoring wells in the area to be optimized to obtain water quality indicators in the area to be optimized;

[0022] Step 302: Perform principal component analysis on the water quality of the area to be optimized to determine the principal components of the groundwater quality in the area;

[0023] Step 303: According to the main components of groundwater quality, the pollution degree of the area to be optimized is obtained through cluster analysis.

[0024] Preferably, the monitoring wells in the area to be optimized are inspected on site and the coordinates are relocated using GPS, water samples are collected in the monitoring wells to measure the conductivity, temperature, pH value and dissolved oxygen content, and soil samples are collected near the monitoring wells, so as to obtain various water quality indicators of the groundwater in the area to be optimized.

[0025] Preferably, the statistical characteristics such as the mean, standard deviation and coefficient of variation of various water quality indicators in the flood season and the dry season are calculated and compared and analyzed respectively, and the correlation coefficient of the same water quality indicator in the flood season and the dry season is calculated at the same time. The water quality data is subjected to principal component analysis using SPSS statistical analysis software, and the water quality components are extracted with the first characteristic threshold value to obtain the eigenvalues, variance contribution rates and initial factor loading matrices, thereby extracting the main components of groundwater quality.

[0026] Preferably, the pollution degree of groundwater is divided into three categories: high pollution area, medium pollution area and low pollution area; and values ​​are assigned to them respectively: 5 points for high pollution area, 3 points for medium pollution area and 1 point for low pollution area.

[0027] Preferably, the groundwater pollution degree and the groundwater protection urgency are multiplied to obtain the groundwater pollution risk; and the groundwater pollution risk level is divided into five levels: low, lower, medium, higher, and high according to the scores from low to high.

[0028] (III) Beneficial effects: The present invention provides a method for optimizing the groundwater dynamic monitoring well network based on pollution susceptibility and risk zoning, and performs dynamic adjustment and optimization according to the degree of groundwater pollution, so that the new groundwater dynamic monitoring well network can obtain sufficient groundwater information data with high accuracy under the premise of using less human and material resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a flowchart of the steps of the groundwater dynamic monitoring well network optimization method based on the pollution susceptibility and risk zoning of the present invention;

[0030] Figure 2 is a detailed flow chart of step 2;

[0031] Figure 3 is a detailed flow chart of step 3;

[0032] Figure 4 This is a schematic diagram of groundwater functional zoning in Guangzhou;

[0033] Figure 5 This is a schematic diagram of the pore water pollution susceptibility level in Guangzhou;

[0034] Figure 6 This is a schematic diagram of the pollution susceptibility level of fissure water in Guangzhou;

[0035] Figure 7 This is a schematic diagram of the urgency level of pore water protection in Guangzhou;

[0036] Figure 8 This is a schematic diagram of the urgency level of fissure water protection in Guangzhou;

[0037] Fig. 9 This is a schematic diagram of the pore water pollution risk level in Guangzhou;

[0038] Fig.10 This is a schematic diagram of the risk level of fissure water pollution in Guangzhou. DETAILED DESCRIPTION

[0039] The present invention is further described in detail below in conjunction with preferred embodiments. More details are elaborated in the following description to facilitate a full understanding of the present invention. However, the present invention can obviously be implemented in a variety of other ways different from the description. Those skilled in the art can make similar generalizations and deductions based on actual application situations without violating the connotation of the present invention. Therefore, the protection scope of the present invention should not be limited by the content of this specific embodiment.

[0040] The accompanying drawings are schematic diagrams of embodiments of the present invention. It should be noted that the drawings are only examples and are not drawn to scale, and should not be used to limit the actual protection scope of the present invention.

[0041] Optimization method of groundwater dynamic monitoring well network based on pollution susceptibility and risk zoning, such as Figure 1 As shown, the specific steps include:

[0042] Step 1: Determine the hydrogeological background and groundwater functional zoning of the area to be optimized.

[0043] Step 2: Analyze the pollution susceptibility of the area to be optimized according to the hydrogeological background and obtain the pollution susceptibility level; and obtain the groundwater protection urgency level according to the pollution susceptibility level and groundwater functional zoning.

[0044] Step 3: Determine the existing monitoring wells in the area to be optimized and take samples from them, analyze the principal components of the water quality of the groundwater in the area to be optimized, and obtain the principal components of the water quality of the groundwater in the area to be optimized; thereby obtaining the degree of groundwater pollution in the area to be optimized.

[0045] Step 4: Obtain the groundwater pollution risk level according to the groundwater pollution degree and groundwater protection urgency level of the area to be optimized.

[0046] Step 5: According to the groundwater pollution risk level, dynamically monitor the optimized area and optimize the monitoring well network.

[0047] More specifically, the step 1 is as follows:

[0048] Conduct a basic status survey of the area to be optimized, including physical geography, topography, vegetation, social economy, geological structure, groundwater type, groundwater recharge, groundwater runoff, groundwater development and utilization history and status, etc. This will provide a clear understanding of the hydrogeological background and groundwater functional zoning of the area to be optimized.

[0049] The method for investigating the basic status of the area to be optimized can be on-site sampling and measurement, or it can be consulting existing data. There is no specific limitation in the present invention, as long as accurate information can be obtained.

[0050] More specifically, Figure 2 As shown, the step 2 specifically includes:

[0051] Step 201: Use the DRASTIC evaluation method to analyze the groundwater pollution susceptibility of the area to be optimized, and quantify the pollution susceptibility level.

[0052] The DRASTIC evaluation method mainly includes two parts: one is to divide the area to be optimized into geological units and select evaluation factors that meet the actual situation according to the hydrogeological background in the area to be optimized; the other is a comprehensive analysis of the relative grading system of DRASTIC.

[0053] The DRASTIC evaluation method includes seven indicators that affect and control the migration of pollutants, namely, depth of groundwater table, net recharge rate, aquifer media, soil media, topography, impact of vadose zone, and conductivity of aquifer. Each indicator is further subdivided into different numerical ranges (numerical parameters) or media types (non-numerical parameters), and the indicator value is used to quantify the impact of the numerical range and / or the media type on groundwater contamination susceptibility, thereby obtaining a groundwater contamination susceptibility index.

[0054] In general, the DRASTIC evaluation method includes the following contents: (1) groundwater pollution vulnerability evaluation factor index system; (2) groundwater pollution vulnerability scoring standard; (3) groundwater pollution vulnerability evaluation weight; (4) groundwater pollution vulnerability evaluation index. Finally, the groundwater pollution vulnerability index is arranged from small to large, and the groundwater pollution vulnerability can be divided into five levels: low groundwater pollution vulnerability (I), low groundwater pollution vulnerability (II), medium groundwater pollution vulnerability (III), high groundwater pollution vulnerability (IV), and high groundwater pollution vulnerability (V).

[0055] Step 202: Obtain the groundwater protection urgency level according to the pollution susceptibility level and groundwater functional zoning.

[0056] The pollution susceptibility level of the optimized area is assigned 1-5 points from low to high; that is, low groundwater pollution susceptibility (I) is 1 point; and so on, high groundwater pollution susceptibility (V) is 5 points. Similarly, the groundwater functional zoning of the optimized area is assigned 1-5 points from low to high importance.

[0057] According to the pollution susceptibility level and groundwater functional zoning of the area to be optimized, the scores of the two are added together to obtain the groundwater protection urgency level reflecting the severity of the pollution consequences. The groundwater protection urgency level is divided into five levels from low to high, namely low (2-3 points), lower (4-5 points), medium (6 points), higher (7-8 points), and high (9-10 points). The higher the score, the higher the urgency of groundwater protection in the area; similarly, the lower the score of the groundwater protection urgency level, the lower the urgency of groundwater protection in the area.

[0058] More specifically, Figure 3 As shown, the step 3 specifically includes:

[0059] Step 301: locate and sample the monitoring wells in the area to be optimized to obtain water quality indicators in the area to be optimized.

[0060] The monitoring wells in the area to be optimized are inspected on site and their coordinates are relocated using GPS. Water samples are collected from the monitoring wells to measure conductivity, temperature, pH value and dissolved oxygen content, and soil samples are collected near the monitoring wells to obtain various water quality indicators of the groundwater in the area to be optimized.

[0061] The specific operation of collecting water samples is: first, take water from the three-tube monitoring well to rinse the Behler tube and the sampling bottle, then use the rinsed Behler tube to collect water samples, and place the collected water samples in the rinsed sampling bottle; respectively measure the conductivity, temperature, pH value and dissolved oxygen content of the collected water samples in the sampling bottle.

[0062] The specific operation of collecting soil samples is as follows: remove the fallen materials and vegetation on the ground surface, and then collect soil samples from the surface layer of 0 to 10 cm. About 500 grams of soil samples are collected near each monitoring well, and plant roots, fallen materials and gravel in the soil samples are removed. 100 grams of soil samples are taken and air-dried for a week until they are free of moisture, and the remaining soil samples are sealed and stored. The dried soil samples are crushed and ground, and soil samples with a particle size of less than 2 mm are screened through a soil sieve. About 0.25 grams of the screened soil sample is placed in a 100mL beaker and 10mL of 10% H2O2 solution (the ratio of H2O2 to water is 1:4) is added. The solution is fully reacted for 1 day to remove the organic matter in the soil sample. If there is a lot of organic matter in the soil sample, 10% H2O2 solution can be appropriately added to fully react until the foam disappears, so as to achieve a better organic matter removal effect. Then add 10 mL of 10% HCl solution, react for 1 day to remove carbonate, remove the supernatant in the beaker after standing, add pure water to adjust the sample to neutrality, let it stand for 1 day, and remove the supernatant again. Add 10 mL of 1 mol / L sodium hexametaphosphate (dispersant) solution to the beaker, shake to fully disperse the soil sample in the solution, and use Mastersizer 2000 laser particle size analyzer to measure the distribution ratio of each particle size.

[0063] Step 302: Perform principal component analysis on the water quality of the area to be optimized to determine the principal components of the groundwater quality in the area.

[0064] The statistical characteristics of water quality indicators such as mean, standard deviation and coefficient of variation in the flood season and dry season were calculated and compared and analyzed respectively. The correlation coefficient of the same water quality indicator in the flood season and dry season was calculated. The principal component analysis of the water quality data was carried out using SPSS statistical analysis software. The water quality components were extracted with the first characteristic threshold, and the eigenvalues, variance contribution rates and initial factor loading matrices were obtained, thereby extracting the main components of groundwater quality.

[0065] The first characteristic threshold is a preset value, which can be selected and modified according to actual conditions, but once determined, it cannot be changed during the same principal component analysis process.

[0066] Step 303: According to the main components of groundwater quality, the pollution degree of the area to be optimized is obtained through cluster analysis.

[0067] According to the main components of water quality in the area to be optimized, cluster analysis was performed to obtain the types of pollutants in different periods and regions, as well as the degree of groundwater pollution caused by each type of pollutant. The groundwater pollution degree was divided into three categories: high pollution area, medium pollution area, and low pollution area; and values ​​were assigned to them respectively: 5 points for high pollution area, 3 points for medium pollution area, and 1 point for low pollution area.

[0068] More specifically, the step 4 is as follows:

[0069] The groundwater pollution level and the groundwater protection urgency are multiplied to obtain the groundwater pollution risk. According to the scores from low to high, the groundwater pollution risk level is divided into five levels: low (2-12 points), lower (15-18 points), medium (20-25 points), higher (27-35 points), and high (40-50 points). The higher the score, the greater the pollution consequences of the area, so it needs to be governed; conversely, the lower the score, the smaller the pollution consequences and the lower the urgency of governance.

[0070] More preferably, the above-mentioned pollution susceptibility level, the groundwater functional zoning, the pollution source level, etc. can be displayed by zoning on the topographic map, which is more intuitive and visible. And the level distribution is a relative value, not an absolute value, and can be selected according to the actual situation of the monitoring area.

[0071] More specifically, the step 5 is as follows:

[0072] According to the groundwater pollution risk level, reference to relevant standards and actual conditions, the density of the groundwater monitoring well network will be dynamically adjusted.

[0073] The dynamic adjustment refers to the real-time adjustment of the density of the groundwater monitoring well network according to the real-time changes in the groundwater pollution risk level. Due to factors such as human production and life, the pollution risk in the same area may change, so the density of monitoring wells in the area will be adjusted to make the distribution of groundwater monitoring wells more reasonable, delete monitoring wells in areas where the original distribution density is too high, and add monitoring wells in areas where the density is too low; appropriately increase the density of monitoring wells in key monitoring areas and reduce the density of monitoring wells in general areas.

[0074] In this invention, referring to relevant standards and combining with actual conditions, the density of groundwater monitoring wells is designed as follows: 5 / 100km in high-risk areas2 ; 3-4 high risk areas / 100km 2 ; 1-2 medium and lower risk areas / 100km 2 .

[0075] More preferably, the groundwater monitoring wells may be bound to the groundwater pollution level, so as to determine the monitoring area of ​​each monitoring well and the monitoring frequency of the monitoring well.

[0076] Specifically, each monitoring well in the monitoring well network is bound to the groundwater pollution level. Each monitoring well is numbered, and the monitoring well number is mapped to the area where the monitoring well is located, that is, the geographical location of each monitoring well needs to be marked. When the groundwater risk level changes, the monitoring wells within the first threshold area of ​​the area will be matched and called. When the groundwater pollution level in a certain area becomes higher, the number of monitoring wells monitoring the area will increase, and the monitoring range of each monitoring well will decrease accordingly according to the increase in the number of increased monitoring wells; at the same time, the monitoring frequency of the monitoring wells will increase. Conversely, when the groundwater pollution level in a certain area becomes lower, the number of monitoring wells monitoring the area will decrease, and the monitoring range of each monitoring well will expand according to the decrease in the number of increased monitoring wells; at the same time, the monitoring frequency of all monitoring wells will increase.

[0077] The first threshold area refers to a circle with the area where the groundwater pollution level changes as the center and the first threshold as the radius. The first threshold can be set according to actual conditions and is not specifically limited here. It should be noted that the size of the first threshold is proportional to the area of ​​the area where the groundwater pollution level changes.

[0078] For example, the area of ​​a region is 100km 2 , when the groundwater pollution level in the area changes from medium risk to high risk. With the area as the center and a radius of 10km, a circle is drawn to obtain the first threshold area, and the monitoring wells within the first threshold area are matched. The number of monitoring wells in the area will change from 2 to 5. Since the number of monitoring wells in the same area has increased, the monitoring range of each monitoring well can be appropriately reduced. The monitoring range of each monitoring well has been reduced from the original 50km 2 becomes 20km 2. For each monitoring well, the monitoring range has become smaller, so the monitoring accuracy has increased accordingly. At the same time, since the monitoring range of the monitoring well has been reduced, the monitoring frequency needs to be increased accordingly, from the original 2 times / day to 5 times / day. More preferably, it is possible to conduct multiple targeted monitoring on one or several monitoring wells where the groundwater pollution level changes more greatly, which can better ensure the accuracy of the monitoring results, while simplifying the monitoring process, reducing costs, and being more efficient.

[0079] The following is a detailed description of the embodiment, which is described by taking the entire Guangzhou city as an example:

[0080] Guangzhou is located in southern China, south-central Guangdong Province and north-central Pearl River Delta. The Xijiang, Beijiang and Dongjiang rivers converge here, close to the lower estuary of the Pearl River Basin. It is a transition zone between the delta plain and the low mountain and hilly area. Guangzhou is about 155km long from south to north and about 106km wide from east to west. The total area of ​​the city is 7434.4km 2 Guangzhou is located in the transition zone between the low mountains in Guangdong and the Pearl River Delta. The terrain slopes from northeast to southwest, and the layered structure of the landform is obvious. The north is dominated by mountains and hills, the middle is dominated by tablelands and terraces, and the south and west are dominated by plains.

[0081] Guangzhou is located on the northern edge of the Pearl River Delta Plain, in the lower reaches of the Dongjiang River, Xijiang River and Beijiang River. It is densely covered with waterways and rivers, and belongs to the water-rich area in the south. The northeast is dominated by mountain rivers, mainly Liuxi River flowing through Conghua District, Huadu District and Baiyun District; the upper reaches are from Longmen County and Zengjiang River flowing through Zengcheng District. The south is the Pearl River Delta river network area, which is mainly a river network formed by the confluence of the lower reaches of the West, North and Dongjiang Rivers and the front and back channels of the Pearl River.

[0082] The basic types of groundwater in Guangzhou are mainly loose rock pore water, covered carbonate cave water, red layer pore fissure water and bedrock fissure water. The total groundwater consumption in the city is composed of residential water, urban public water, industrial water, agricultural water and ecological environment water, accounting for about 19.63%, 3.02%, 52.42% and 24.93% of the total groundwater consumption in the city respectively. Figure 4 As shown in the figure, groundwater is zoned according to its function to obtain a groundwater functional zoning map.

[0083] According to the different types of groundwater monitored, the monitoring wells are divided into fissure water monitoring wells and pore water monitoring wells, and different types of monitoring well networks are monitored and optimized separately.

[0084] like Figure 5 , Figure 6As shown in the figure, ArcGIS was used to make pollution susceptibility maps for pore water and fissure water respectively. The groundwater pollution susceptibility in Guangzhou is divided into 5 levels, where Ⅰ represents the lowest groundwater pollution susceptibility and Ⅴ represents the highest groundwater pollution susceptibility. The values ​​are relative values ​​of susceptibility to pollution, not absolute pollution quantities.

[0085] According to the underground pore water and fissure water pollution susceptibility grade table and pollution susceptibility distribution map, the area proportion of each grade was calculated, and the pollution susceptibility grades of pore water and fissure water in Guangzhou were obtained as shown in Table 1.

[0086] Table 1. Pore water and fissure water pollution grade in Guangzhou

[0087] Stain resistance level Proportion of pore water susceptible to pollution Proportion of fracture water contamination-prone space Ⅰ 9.05％ 13.18％ Ⅱ 20.90％ 29.97％ Ⅲ 43.15％ 30.96％ Ⅳ 24.64％ 11.08％ Ⅴ 2.26％ 14.82％

[0088] As shown in Table 1, the distribution area of ​​medium pollution susceptibility (III) in Guangzhou groundwater is the largest, including 43.15% of pore water and 30.96% of fissure water. Whether it is pore water or fissure water, more than 1 / 4 of the area is in the situation of high pollution susceptibility (IV) and high pollution susceptibility (V), among which the area occupied by high pollution susceptibility (V) of fissure water is 6.5 times that of pore water with the same pollution susceptibility.

[0089] The pollution susceptibility level map and the groundwater functional zoning map are superimposed to generate a groundwater protection urgency map, such as Figure 7 , Figure 8 shown.

[0090] The principal component analysis method was used to compare with the water quality standards and analyze the pollution degree of groundwater in different regions. Cluster analysis was performed based on the principal components extracted from the samples, and the main pollutants in different regions were distinguished according to different principal components. The ArcGIS software was used to perform Thiessen polygon spatial analysis to obtain the spatial distribution of groundwater with different pollution types in Guangzhou. The statistical characteristics such as the mean, standard deviation and coefficient of variation of various water quality indicators in the flood season and dry season were calculated and compared, and the correlation coefficients of the same water quality indicators in the flood season and dry season were calculated, as shown in Tables 2 and 3.

[0091] Table 2 Comparison of statistical characteristics of various indicators of pore water in flood season and dry season

[0092]

[0093]

[0094] Table 3 Comparison of statistical characteristics of various indicators of fissure water in flood season and dry season

[0095]

[0096]

[0097] Using SPSS statistical analysis software, we first conducted principal component analysis on the water quality data of pore water in the dry season. Combined with the actual situation, we used the eigenvalue of 0.95 as the first extraction threshold to extract the principal components, and obtained the eigenvalue and variance contribution rate table and the initial factor loading matrix table as shown in Tables 4 and 5.

[0098] Table 4. Pore water characteristic values ​​and variance contribution rates during dry season

[0099]

[0100]

[0101] Table 5 Initial factor loading matrix of pore water in dry season

[0102]

[0103]

[0104] According to principal component analysis, a total of 5 principal components are extracted, as shown in formula (1) to formula (5):

[0105] y1=0.232x1-0.004x2-0.015x3+…-0.146x 17 (1)

[0106] y2=-0.014x1-0.418x2+0.348x3+…+0.355x 17 (2)

[0107] y3=0.331x1-0.274x2+0.107x3+…+0.035x 17 (3)

[0108] y4=0.070x1+0.414x2+0.485x3+…+0.252x 17 (4)

[0109] y5=-0.253x1-0.335x2+0.320x3+…-0.273x 17 (5).

[0110] Therefore, the comprehensive expression of the principal component score is shown in formula (6), from which the comprehensive water quality score of the pore water at each sampling point in the dry season can be calculated. The higher the comprehensive water quality score, the higher the degree of groundwater pollution; the lower the comprehensive water quality score, the lower the degree of groundwater pollution.

[0111] F=0.433x1+0.123x2+0.104x3+0.068x4+0.058x5 (6).

[0112] Similarly, principal component analysis can be performed on the dry season fissure water, the flood season pore water, and the flood season fissure water, and their scores can be calculated to obtain the comprehensive water quality score for each period, thereby obtaining the degree of groundwater pollution in different periods.

[0113] The groundwater pollution risk level is obtained by multiplying the severity of the pollution consequences by the pollution probability, that is, the product of the groundwater pollution degree and the groundwater protection urgency level, as shown in Table 6. Fig. 9 , Fig.10 shown.

[0114] Table 6 Grading table of pollution risk assessment indicators

[0115]

[0116] With reference to relevant standards and in combination with actual conditions, the density of groundwater monitoring wells is designed to be: 5 / 100km in high-risk areas 2 ; 3-4 high risk areas / 100km 2 ; 1-2 medium and lower risk areas / 100km 2 Based on the pollution risk assessment results, a higher observation density was set in areas with high pollution risk, and a lower observation density was set in areas with low pollution risk.

[0117] There were originally 250 monitoring wells, and after optimization, there are 192 water quality monitoring wells in total, of which 152 original monitoring wells are retained, 98 damaged or redundant wells are removed, and 40 new monitoring wells are built. After optimization, the distribution of water quality monitoring wells is more reasonable, monitoring wells are deleted in areas with too high density, and monitoring wells are added in areas with too low density; the density of wells in key monitoring areas is appropriately increased, and the density of wells in general areas is reduced. At the same time, the monitoring type of groundwater at the well location is more consistent with the distribution of groundwater types.

[0118] The present invention provides a groundwater dynamic monitoring well network optimization method based on pollution susceptibility and risk zoning, and performs dynamic adjustment and optimization according to the degree of groundwater pollution, so that a new groundwater dynamic monitoring well network can obtain sufficient groundwater information data with high accuracy under the premise of using less human and material resources.

[0119] The above content is an explanation of the preferred embodiments of the present invention, which can help those skilled in the art to more fully understand the technical solution of the present invention. However, these embodiments are merely illustrative, and it cannot be determined that the specific implementation methods of the present invention are limited to the description of these embodiments. For ordinary technicians in the technical field to which the present invention belongs, without departing from the concept of the present invention, several simple deductions and transformations can be made, which should be regarded as belonging to the protection scope of the present invention.

Claims

1. A groundwater dynamic monitoring well network optimization method based on pollution susceptibility and risk zoning, characterized in that: Specifically include: Step 1, determine the hydrogeological background and groundwater functional zoning of the area to be optimized; Step 2: Analyze the pollution susceptibility of the area to be optimized according to the hydrogeological background, and obtain the pollution susceptibility level; and obtain the groundwater protection urgency level according to the pollution susceptibility level and groundwater functional zoning; Step 3, determine the existing monitoring wells in the area to be optimized and take samples from them, analyze the principal components of the water quality of the groundwater in the area to be optimized, and obtain the principal components of the water quality of the groundwater in the area to be optimized; thereby obtaining the degree of groundwater pollution in the area to be optimized; Step 4: Obtain the groundwater pollution risk level according to the groundwater pollution degree and groundwater protection urgency level of the area to be optimized; Step 5: According to the groundwater pollution risk level, dynamically monitor the optimized area and optimize the monitoring well network.

2. The method for optimizing groundwater dynamic monitoring well network based on pollution susceptibility and risk zoning according to claim 1 is characterized in that: The step 1 specifically includes: conducting a basic status survey of the area to be optimized to understand the hydrogeological background and groundwater functional zoning of the area to be optimized.

3. The method for optimizing groundwater dynamic monitoring well network based on pollution susceptibility and risk zoning according to claim 1 is characterized in that: The step 2 specifically includes: Step 201, using the DRASTIC evaluation method to analyze the groundwater pollution susceptibility of the area to be optimized, and quantifying the pollution susceptibility level; Step 202: Obtain the groundwater protection urgency level according to the pollution susceptibility level and groundwater functional zoning.

4. The method for optimizing groundwater dynamic monitoring well network based on pollution susceptibility and risk zoning according to claim 3 is characterized in that: The DRASTIC evaluation method is subdivided into different value ranges or media types, and an index value is used to quantify the impact of the value range and / or the media type on groundwater contamination susceptibility to obtain a groundwater contamination susceptibility index; The groundwater pollution susceptibility index is arranged from small to large, and the groundwater pollution susceptibility is divided into five levels: low groundwater pollution susceptibility, low groundwater pollution susceptibility, medium groundwater pollution susceptibility, high groundwater pollution susceptibility, and high groundwater pollution susceptibility.

5. The method for optimizing groundwater dynamic monitoring well network based on pollution susceptibility and risk zoning according to claim 3 is characterized in that: The pollution susceptibility level of the optimized area is assigned 1-5 points from low to high, and the groundwater functional zoning of the optimized area is assigned 1-5 points from low to high in importance; According to the pollution susceptibility level and groundwater functional zoning of the area to be optimized, the scores of the two are added together to obtain the groundwater protection urgency level reflecting the severity of the pollution consequences; The groundwater protection urgency level is divided into five levels from low to high, with scores ranging from 2 to 3 points for low, 4 to 5 points for lower, 6 points for medium, 7 to 8 points for higher, and 9 to 10 points for high.

6. The method for optimizing groundwater dynamic monitoring well network based on pollution susceptibility and risk zoning according to claim 1 is characterized in that: The step 3 specifically includes: Step 301: locate and sample the monitoring wells in the area to be optimized to obtain water quality indicators in the area to be optimized; Step 302: Perform principal component analysis on the water quality of the area to be optimized to determine the principal components of the groundwater quality in the area; Step 303: According to the main components of groundwater quality, the pollution degree of the area to be optimized is obtained through cluster analysis.

7. The method for optimizing groundwater dynamic monitoring well network based on pollution susceptibility and risk zoning according to claim 6 is characterized in that: The monitoring wells in the area to be optimized are inspected on site and their coordinates are relocated using GPS. Water samples are collected from the monitoring wells to measure conductivity, temperature, pH value and dissolved oxygen content, and soil samples are collected near the monitoring wells to obtain various water quality indicators of the groundwater in the area to be optimized.

8. The method for optimizing groundwater dynamic monitoring well network based on pollution susceptibility and risk zoning according to claim 6, characterized in that: The statistical characteristics of water quality indicators such as mean, standard deviation and coefficient of variation in the flood season and dry season were calculated and compared and analyzed respectively. The correlation coefficient of the same water quality indicator in the flood season and dry season was calculated. The principal component analysis of the water quality data was carried out using SPSS statistical analysis software. The water quality components were extracted with the first characteristic threshold, and the eigenvalues, variance contribution rates and initial factor loading matrices were obtained, thereby extracting the main components of groundwater quality.

9. The method for optimizing groundwater dynamic monitoring well network based on pollution susceptibility and risk zoning according to claim 6, characterized in that: The pollution degree of groundwater is divided into three categories: high pollution area, medium pollution area and low pollution area; and values ​​are assigned to them respectively: 5 points for high pollution area, 3 points for medium pollution area and 1 point for low pollution area.

10. The method for optimizing groundwater dynamic monitoring well network based on pollution susceptibility and risk zoning according to claim 1, characterized in that: The groundwater pollution degree and the groundwater protection urgency are multiplied to obtain the groundwater pollution risk; the groundwater pollution risk level is divided into five levels from low to high, including 2-12 points for low, 15-18 points for lower, 20-25 points for medium, 27-35 points for higher, and 40-45 points for high.

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