Method for evaluating vulnerability of underground water nitrate pollution

Abstract

The invention discloses a vulnerability evaluation method for underground water nitrate pollution. The method comprises the following steps: selecting nitrate pollution vulnerability evaluation factors, respectively carrying out range and category division on the nitrate pollution vulnerability evaluation factors, rating the vulnerability, and giving a corresponding score according to a rating result; according to the influence of different nitrate pollution vulnerability evaluation factors on the vulnerability, a theoretical weight is given, a DITAPH model is constructed, and a DITAPH index is obtained; comparing the relationship between the theoretical weight and the effective weight of the nitrate pollution vulnerability evaluation factor by adopting a single-parameter sensitivity analysis method, and correcting the weight of each evaluation factor; and recalculating the DITAPH index by using the corrected weight, performing grade division on the DITAPH index, and drawing an NVZs graph of the underground water nitrate fragile region. According to the method, the vulnerability of underground water to nitrate pollution can be evaluated, and the NVZs graph of the underground water nitrate vulnerable area can be drawn.

Description

Technical Field

[0001] The invention relates to the field of engineering technology, and in particular to a vulnerability assessment method for groundwater nitrate pollution. Background Art

[0002] Nitrate is a ubiquitous contaminant in groundwater. Non-point source nitrate pollution has been identified as one of the main causes of groundwater quality deterioration and may cause significant changes in groundwater geochemistry. Long-term exposure to high concentrations of nitrate can cause harm to human health, such as blue baby syndrome, hemoglobinemia, thyroid and ovarian diseases. Nitrate pollution has become an ecological and health problem facing the world.

[0003] Under natural conditions, the nitrate content in aquifers is generally low. However, under the influence of human activities, the nitrate content in groundwater will increase significantly. The main anthropogenic sources of nitrate pollution include domestic and industrial wastewater discharge, excessive use of nitrogen fertilizers and pesticides, and infiltration of animal manure and landfill leachate. Excessive nitrates enter surface water through runoff or groundwater, causing eutrophication of water bodies and excessive reproduction of algae, leading to the degradation of aquatic ecosystems and unsustainable use of water resources.

[0004] The impact of hydrogeological conditions and human activity intensity in different regions on groundwater nitrate pollution is also significantly different. Groundwater vulnerability characterizes the sensitivity of the groundwater system to humans and (or) nature. Groundwater vulnerability is divided into inherent vulnerability of groundwater and special vulnerability of groundwater. Intrinsic vulnerability reflects the inherent properties of the aquifer, which is the ease with which the groundwater system is polluted under the influence of natural factors; special vulnerability refers to the ease with which the groundwater system is polluted by a certain (type) of pollutants under the combined action of natural and human factors. Conducting groundwater vulnerability assessment can identify areas that are prone to pollution and areas that are not prone to pollution, and provide a scientific basis for the rational development, utilization and protection of groundwater.

[0005] The DRASTIC method was proposed by the United States Environmental Protection Agency (USEPA) in 1985 and has become one of the most widely used methods for inherent vulnerability assessment. The method selects seven evaluation parameters: groundwater depth (D), net recharge (R), aquifer medium (A), soil medium (S), terrain slope (T), influence of the vadose zone (I) and hydraulic conductivity (C), and weights the relative importance of pollution potential accordingly based on these parameters. Although this method has been widely used, many scholars have found that the DRASTIC model has certain defects in practical applications. For example, the soil is actually part of the vadose zone, and detailed information on the soil medium (S) is not easy to obtain; the two factors of aquifer medium (A) and aquifer permeability (C) are repeated, and the rating of the hydraulic conductivity factor (which increases with the increase of groundwater flow velocity) reflects the system's ability to transport pollutants through the saturated zone, and does not affect the ease with which pollutants enter the groundwater from the surface; the parameter weight distribution is unreasonable; the attenuation capacity of the unsaturated zone is overemphasized; the rating of net recharge (R) (which increases with the increase of recharge volume) reflects the ability of the recharge water to bring pollutants to the saturated zone, and does not reflect the ability of the recharge water to dilute the pollutants if it is large enough; the net recharge (R) will vary due to different factors such as soil medium, evapotranspiration, topography, infiltration, vegetation cover, runoff, precipitation, freeze-thaw conditions, soil permeability and porosity, and these data are often not accurately obtained.

[0006] In 1991, the Council of the European Communities issued the European Union Directive "The Nitrates Directive (91 / 676 / EEC)" in response to the impact of nitrate pollution from agricultural sources on the environment and health. The directive requires member states to designate nitrate vulnerable zones (NVZs). In NVZs, farmers must follow mandatory measures such as limiting the application of nitrogen fertilizers and animal manure in the action plan to prevent nitrate leaching and runoff, but the directive does not provide a unified method for delineating NVZs. In the past few decades, many scholars have conducted extensive research on vulnerability assessment methods for nitrate pollution, selection of assessment parameters, assignment of parameter ratings and weights, vulnerability zoning and risk mapping.

[0007] Foreign scholars have improved and established a variety of nitrate pollution vulnerability assessment methods based on the DRASTIC model, such as DRASTIC-AHP (hierarchy analysis method), DRASTICA (the second "A" refers to the impact of human activities), DRASTIC model optimization model based on genetic algorithm (GA), groundwater vulnerability mapping based on generalized simplified gradient (GRG) method, and LU-IV model. The above studies show that the delineation of NVZs is a useful tool to help governments formulate water resources management plans and related policies. However, some studies have also confirmed that if NVZs are not properly delineated, the effectiveness of nitrate pollution reduction actions will be affected.

[0008] The problem of groundwater nitrate pollution in China is becoming increasingly serious, but there are few studies on the vulnerability assessment and NVZs division of groundwater nitrate pollution. Ma Lin et al. used groundwater nitrate pollution data and nitrogen and phosphorus leaching characteristics of farmland in agricultural areas to preliminarily divide my country's nitrate vulnerable areas and potential vulnerable areas. The delineation results of this study characterize the general distribution characteristics of NVZs across the country, and there is still a large degree of uncertainty. Yan Yani et al. established the DRASTIPO model. Based on the parameters of the DRASTIC model, the model added two indicators, pollutant input intensity (p) and soil organic matter content (O), and used the principal component-factor analysis method to determine the indicator weights. The vulnerability of groundwater nitrate pollution in the Shaying River Basin was evaluated. Detailed information on soil organic matter content (O) in this model is not easy to obtain. Liao Man et al. improved the traditional DRASTIC evaluation model: first, given the flat terrain and small changes in terrain slope in the study area, the influence of terrain slope was ignored; second, given the duplication between the water-richness (A) and the permeability coefficient (C) of the aquifer, the permeability coefficient (C) was not considered; third, considering the impact of human activities, the land use type (L) and groundwater extraction (E) were added. Finally, the DRASILE model was established to evaluate the vulnerability of groundwater nitrate pollution in the plain area of ​​the Huaihe River Basin. The selection of evaluation parameters of this model is based on the hydrogeological conditions of the study area and has certain limitations.

[0009] At present, no relevant department in my country has given a unified method for vulnerability assessment of groundwater nitrate pollution and delineation of NVZs, nor has it established nutrient optimization management and non-point source pollution prevention and control plans for nitrate vulnerable areas. Summary of the invention

[0010] In order to solve the above technical problems, the present invention proposes a vulnerability assessment method for groundwater nitrate pollution, which incorporates natural factors such as geology and hydrogeology (groundwater level depth, vadose zone lithology, terrain slope, rainfall and aquifer thickness) and human activity factors (land use and population density) into the vulnerability assessment of groundwater nitrate pollution, and proposes a vulnerability assessment model for groundwater nitrate pollution (DITAPH model), which provides technical support and scientific basis for non-point source pollution control and nutrient optimization management programs in regional nitrate vulnerable areas.

[0011] To achieve the above object, the present invention provides a vulnerability assessment method for groundwater nitrate pollution, comprising:

[0012] Select nitrate pollution vulnerability assessment factors, divide the nitrate pollution vulnerability assessment factors into ranges and categories, rate the vulnerability of different ranges and categories, and assign corresponding scores according to the rating results;

[0013] According to the influence of different nitrate pollution vulnerability assessment factors on vulnerability performance, the theoretical weights are given, the DITAPH model is constructed, and the DITAPH index is obtained;

[0014] The single parameter sensitivity analysis method is used to compare the relationship between the theoretical weight and the effective weight of the nitrate pollution vulnerability assessment factor, and the weight of each assessment factor is corrected;

[0015] The DITAPH index was recalculated using the revised weights, the DITAPH index was graded, and a groundwater nitrate vulnerable zone NVZs map was drawn based on the classification results.

[0016] Preferably, the nitrate pollution vulnerability assessment factors include groundwater level depth, vadose zone lithology, terrain slope, rainfall, aquifer thickness and human activities; wherein human activities include land use and population density.

[0017] Preferably, each nitrate pollution vulnerability assessment factor is divided into ranges and categories, and then a corresponding score is assigned according to the rating results of the vulnerability performance of each range and category. The score range is 1-10, where the largest vulnerability performance is assigned 10 points and the smallest vulnerability performance is assigned 1 point.

[0018] Preferably, theoretical weights are given according to the influence of different nitrate pollution vulnerability assessment factors on the vulnerable performance, and the range of the theoretical weights is 1-5, wherein the theoretical weight with the greatest influence on the vulnerable performance is 5, and the theoretical weight with the least influence on the vulnerable performance is 1.

[0019] Preferably, the DITAPH model is:

[0020] DI=Dr×Dw+Ir×Iw+Tr×Tw+Ar×Aw+Pr×Pw+Hr×Hw

[0021] Among them, DI is the DITAPH index, D is the depth of groundwater level, I is the lithology of the aeration zone, T is the terrain slope, P is the rainfall, A is the thickness of the aquifer, H is the human activity, and r and w are the score and weight assigned to each parameter, respectively.

[0022] Preferably, the effective weight is calculated as follows:

[0023]

[0024] Where W is the effective weight of each parameter; P r is the score; P w is the theoretical weight; V is the vulnerability index;

[0025] If the effective weight is greater than the theoretical weight, the contribution of the corresponding assessment factor to the vulnerability index is greater.

[0026] Preferably, the DITAPH index is graded using a four-point method, and the classification results include low vulnerability, lower vulnerability, higher vulnerability and high vulnerability.

[0027] Preferably, the method further comprises:

[0028] The Pearson correlation coefficient was used to analyze the correlation between the measured groundwater nitrate concentration and the DITAPH index to verify the accuracy of the groundwater nitrate vulnerable zone NVZs map division.

[0029] Preferably, the Pearson correlation coefficient is calculated as follows:

[0030]

[0031] Where R is the Pearson correlation coefficient; n is the data point; ρ is the nitrate concentration in mg / L; DI is the DITAPH index;

[0032] The R value ranges from -1 to 1, with 1 indicating a perfect positive correlation, -1 indicating a perfect negative correlation, and 0 indicating no linear relationship.

[0033] Compared with the prior art, the present invention has the following advantages and technical effects:

[0034] The DITAPH model for vulnerability assessment of groundwater nitrate pollution proposed in the present invention takes into account both regional hydrogeological conditions and the characteristics of nitrate pollution being affected by human activities. The weights are calculated by comparing the relationship between the theoretical weights and effective weights of vulnerability assessment factors through a single-parameter sensitivity analysis method, and the weights of each assessment factor are corrected accordingly, thereby realizing the vulnerability assessment of groundwater to nitrate pollution and the delineation of nitrate vulnerable areas. This model can provide technical support and scientific basis for regional groundwater nitrate pollution prevention and control, as well as non-point source pollution control and nutrient optimization management programs in regional nitrate vulnerable areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0036] Figure 1 This is a flow chart of a vulnerability assessment method for groundwater nitrate pollution in an embodiment of the present invention;

[0037] Figure 2 This is the NVZs diagram of the vulnerability zones of groundwater nitrate pollution in the DITAPH model evaluation system in the embodiment of the present invention. DETAILED DESCRIPTION

[0038] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0039] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0040] The present invention proposes a vulnerability assessment method for groundwater nitrate pollution, such as Figure 1 ,include:

[0041] Select nitrate pollution vulnerability assessment factors, divide the nitrate pollution vulnerability assessment factors into ranges and categories, rate the vulnerability of different ranges and categories, and assign corresponding scores according to the rating results;

[0042] Furthermore, nitrate pollution vulnerability assessment factors include groundwater level depth, vadose zone lithology, terrain slope, rainfall, aquifer thickness (or water richness) and human activities, among which human activities include land use and population density.

[0043] The rating results of the vulnerability of each nitrate pollution vulnerability assessment factor are assigned corresponding scores ranging from 1 to 10; among them, the score with the greatest impact on vulnerability performance is 10, and the score with the smallest impact on vulnerability performance is 1; the weight range is 1-5, among which the weight with the greatest impact on vulnerability performance is 5, and the weight with the smallest impact on vulnerability performance is 1.

[0044] According to the influence of different nitrate pollution vulnerability assessment factors on vulnerability performance, the theoretical weights are given, the DITAPH model is constructed, and the DITAPH index (DI) is obtained;

[0045] DITAPH is a model constructed by this method. The parameters selected in this model are the combination of the first letters of the groundwater level depth (D), lithology of the aeration zone (I), terrain slope (T), rainfall (P), aquifer thickness (A), and human activities (H).

[0046] Furthermore, the DITAPH model is:

[0047] DI=Dr×Dw+Ir×Iw+Tr×Tw+Ar×Aw+Pr×Pw+Hr×Hw

[0048] Among them, DI is the DITAPH index, D is the depth of groundwater level, I is the lithology of the aeration zone, T is the terrain slope, P is the rainfall, A is the thickness of the aquifer, H is the human activity, and r and w are the score and weight assigned to each parameter, respectively.

[0049] The higher the DI, the greater the vulnerability of groundwater to nitrate pollution.

[0050] The single parameter sensitivity analysis method was used to compare the relationship between the theoretical weight and the effective weight of the nitrate pollution vulnerability assessment factor, and the weight of each assessment factor was corrected.

[0051] Furthermore, the effective weight is calculated as follows:

[0052]

[0053] Where W is the effective weight of each parameter; P r is the score; P w is the theoretical weight; V is the vulnerability index;

[0054] If the effective weight is greater than the theoretical weight, the contribution of the corresponding assessment factor to the vulnerability index is greater.

[0055] The DITAPH index was recalculated using the revised weights, the DITAPH index was graded, and a groundwater nitrate vulnerable zone NVZs map was drawn based on the classification results.

[0056] Furthermore, the DITAPH index is divided into four levels, including low vulnerability, lower vulnerability, higher vulnerability and high vulnerability.

[0057] Finally, the Pearson correlation coefficient was used to analyze the correlation between the measured groundwater nitrate concentration and the DITAPH index to verify the accuracy of the NVZs map division of groundwater nitrate vulnerable zones.

[0058] The calculation method of Pearson correlation coefficient is:

[0059]

[0060] Where R is the Pearson correlation coefficient; n is the data point; ρ is the nitrate concentration in mg / L; DI is the DITAPH index;

[0061] The R value ranges from -1 to 1, with 1 indicating a perfect positive correlation, -1 indicating a perfect negative correlation, and 0 indicating no linear relationship.

[0062] In order to more clearly express the technical solution of the present invention, the following specific embodiments are provided to introduce the solution:

[0063] Step 1: Select vulnerability assessment factors for groundwater nitrate pollution.

[0064] There are many factors that affect the accuracy of groundwater vulnerability assessment results: the representativeness of the assessment factors, the accuracy and detail of the parameter-related data, the rationality of the interval (category) division of each assessment factor, and the selection of the score value and weight, etc. Therefore, the present invention selects the vulnerability assessment factor of groundwater nitrate pollution based on the above-mentioned influencing factors.

[0065] The nitrate pollution vulnerability assessment factors were selected, including five parameters: groundwater table depth (D), lithology of the aeration zone (I), terrain slope (T), rainfall (P) and aquifer thickness (A) to reflect the inherent vulnerability of groundwater; two human influence (H) parameters, land use (LU) and population density (PD), reflect the impact of human activities on the vulnerability of groundwater nitrate pollution.

[0066] (1) Groundwater depth (D): refers to the depth from the surface to the groundwater level. It is an important factor that determines the distance that pollutants must migrate before reaching the saturated zone and the time that pollutants are in contact with the surrounding medium. Generally speaking, the greater the groundwater depth, the longer the distance that pollutants must migrate, the longer the time that pollutants are in contact with the surrounding medium, the more opportunities for pollutants to decay, and the less susceptible the aquifer is to pollution.

[0067] (2) Unsaturated zone lithology (I): The unsaturated zone refers to the unsaturated zone or discontinuous saturated zone above the water table. The unsaturated zone is a channel for the migration of recharge water to the aquifer. The type of medium in the unsaturated zone controls the seepage path of the recharge water, determines the time required for pollutants to reach the aquifer, and affects the occurrence of dilution, adsorption and degradation during the migration process. The lithology of the unsaturated zone (I) is an important factor reflecting the amount of pollutants and their attenuation capacity, and has a high impact on the vulnerability of aquifers. The scoring of the unsaturated zone medium takes into account the development of cracks, stratification, and caves in the consolidated rock medium, and the particle size, sorting, and fine particle content of the unconsolidated rock medium.

[0068] (3) Terrain slope (T): It is an important factor that reflects whether pollutants are lost through surface runoff or seep into the ground. Relatively flat areas are more conducive to the infiltration of recharge water and are more likely to pollute groundwater.

[0069] (4) Rainfall (P): It is an indicator of aquifer recharge in the form of annual precipitation. Using rainfall (P) instead of net recharge (R) in the DRAST1C model avoids duplication and confusion with the overlying aeration zone medium factor. The greater the rainfall, the more infiltration water, and the more pollutants brought to the phreatic aquifer by the recharge water.

[0070] (5) Aquifer water richness (A): Aquifer vulnerability is affected by the dilution capacity of groundwater. Generally speaking, the dilution capacity mainly depends on the water richness, water supply and thickness of the aquifer. Usually, accurate data on the water richness and water supply of aquifers are difficult to obtain. If there is abundant borehole data in the study area and reliable aquifer thickness data can be obtained, then it is best to use aquifer thickness to reflect the dilution capacity of groundwater. If sufficient borehole data cannot be obtained, the water richness of the aquifer can also be selected as the evaluation factor of the dilution capacity of the aquifer. The weaker the water richness, the worse the dilution capacity.

[0071] (6) Human activities (H): The intensity of human activities on groundwater nitrate pollution is reflected by two parameters: land use (LU) and population density (PD). First, the regional land use types are divided, and then the urban areas are further divided into different levels according to the population density. Land use (LU) reflects how humans transform and use land, and is an important environmental parameter for identifying the impact of human activities. Land use type has a significant impact on the type, amount and pollution intensity of pollutants, and has a dominant influence on the vulnerability of groundwater nitrate pollution. Population density (PD) is an important environmental parameter for identifying the intensity of human activities. Groundwater nitrate pollution is affected by the population density of human settlements. The higher the population density, the greater the amount of sewage generated, and the greater the possibility of groundwater pollution.

[0072] Step 2: Divide each evaluation factor into ranges and categories, and then rate them according to the vulnerability of each range (category) and assign corresponding scores (scores 1-10), as shown in Tables 1 and 2.

[0073] Table 1

[0074]

[0075]

[0076] Table 2

[0077]

[0078] Step 3: According to the influence of each evaluation factor on the vulnerability of groundwater nitrate pollution, a theoretical weight (weight range 1-5) is given. As shown in Table 3, the weight is assigned according to the influence on the vulnerability performance, with the largest weight being 5 and the smallest weight being 1.

[0079] Table 3

[0080]

[0081] Step 4: Calculate and obtain the DITAPH index (DI) based on the DITAPH model formula.

[0082] The calculation formula is as follows:

[0083] DI=Dr×Dw+Ir×Iw+Tr×Tw+Ar×Aw+Pr×Pw+Hr×Hw

[0084] Where DI is the DITAPH index; r and w are the score and weight assigned to each parameter, respectively.

[0085] The higher the DI, the greater the vulnerability of the groundwater.

[0086] Step 5: Use the single parameter sensitivity analysis method to compare the relationship between the theoretical weight and the effective weight of the vulnerability assessment factor, and modify the weight of each assessment factor accordingly.

[0087] The effective weight (W) is calculated as follows:

[0088]

[0089] Where W is the effective weight of each parameter, P r -score, P w -Theoretical weight, V-vulnerability index.

[0090] The effective weight is affected by the theoretical weight and rating of each individual evaluation factor. If the effective weight is greater than the theoretical weight, the corresponding evaluation factor contributes more to the vulnerability index.

[0091] Step 6: Use the revised weights to recalculate the DITAPH index (DI), and use the quartile method to divide the DI into four levels, that is, divide NVZs into low vulnerability, lower vulnerability, higher vulnerability and high vulnerability, and draw a groundwater NVZs map.

[0092] Step 7: Use the Pearson correlation coefficient (R) to analyze the correlation between the measured groundwater nitrate concentration and the DITAPH index (DI) to verify the accuracy of the NVZs division. The Pearson correlation coefficient (R) calculation formula is as follows:

[0093]

[0094] Where, R is Pearson correlation coefficient; n is data point, ρ is nitrate concentration (mg / L); DI is DITAPH index; R value is between -1 and 1, 1 indicates perfect positive correlation, -1 indicates perfect negative correlation, and 0 indicates no linear relationship.

[0095] The DITAPH model for vulnerability assessment of groundwater nitrate pollution proposed in this example takes into account both the regional hydrogeological conditions and the characteristics of nitrate pollution affected by human activities. The hydrogeological parameters selected are: groundwater level depth (D), lithology of the aeration zone (I), terrain slope (T), rainfall (P) and aquifer thickness (A); the human impact (H) parameters are: land use (LU) and population density (PD), such as Figure 2 ; The DITAPH model for vulnerability assessment of groundwater nitrate pollution proposed in this embodiment calculates the weights by comparing the relationship between the theoretical weights and effective weights of the vulnerability assessment factors through a single-parameter sensitivity analysis method, and corrects the weights of each assessment factor accordingly.

[0096] This embodiment is based on the characteristics of groundwater nitrate pollution and combines the concept of source-path-target in groundwater vulnerability assessment to construct a DITAPH model to achieve groundwater vulnerability assessment to nitrate pollution and delineation of nitrate vulnerable areas. It incorporates natural factors such as hydrogeology (groundwater table depth, vadose zone lithology, terrain slope, rainfall and aquifer thickness) and human activities (land use and population density) into the vulnerability assessment of groundwater nitrate pollution, and proposes a DITAPH model for vulnerability assessment of nitrate pollution. The model can evaluate and map the vulnerability of groundwater to nitrate pollution and accurately delineate nitrate vulnerable areas. It can provide technical support and scientific basis for regional groundwater nitrate pollution prevention and control, as well as non-point source pollution control and nutrient optimization management programs in nitrate vulnerable areas.

[0097] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A vulnerability assessment method for groundwater nitrate contamination, It is characterized in that include: Select nitrate pollution vulnerability assessment factors, divide the nitrate pollution vulnerability assessment factors into ranges and categories, rate the vulnerability of different ranges and categories, and assign corresponding scores according to the rating results; According to the influence of different nitrate pollution vulnerability assessment factors on vulnerability performance, the theoretical weights are given, the DITAPH model is constructed, and the DITAPH index is obtained; The single parameter sensitivity analysis method is used to compare the relationship between the theoretical weight and the effective weight of the nitrate pollution vulnerability assessment factor, and the weight of each assessment factor is corrected; The DITAPH index was recalculated using the revised weights, the DITAPH index was graded, and a groundwater nitrate vulnerable zone NVZs map was drawn based on the classification results.

2. The vulnerability assessment method for groundwater nitrate contamination according to claim 1, It is characterized in that The nitrate pollution vulnerability assessment factors include groundwater level depth, vadose zone lithology, terrain slope, rainfall, aquifer thickness and human activities; among which human activities include land use and population density.

3. The vulnerability assessment method for groundwater nitrate contamination according to claim 2, It is characterized in that Each nitrate pollution vulnerability assessment factor is divided into ranges and categories, and then a corresponding score is assigned according to the rating results of the vulnerability performance of each range and category. The score range is 1-10, among which the largest vulnerability performance is assigned 10 points and the smallest vulnerability performance is assigned 1 point.

4. The vulnerability assessment method for groundwater nitrate contamination according to claim 3, It is characterized in that Theoretical weights are given according to the influence of different nitrate pollution vulnerability assessment factors on the vulnerable performance, and the range of the theoretical weights is 1-5, wherein the theoretical weight with the greatest influence on the vulnerable performance is 5, and the theoretical weight with the least influence on the vulnerable performance is 1.

5. The vulnerability assessment method for groundwater nitrate contamination according to claim 1, It is characterized in that The DITAPH model is: DI=Dr×Dw+Ir×Iw+Tr×Tw+Ar×Aw+Pr×Pw+Hr×Hw Among them, DI is the DITAPH index, D is the depth of groundwater level, I is the lithology of the aeration zone, T is the terrain slope, P is the rainfall, A is the thickness of the aquifer, H is the human activity, and r and w are the score and weight assigned to each parameter, respectively.

6. The vulnerability assessment method for groundwater nitrate contamination according to claim 1, It is characterized in that The calculation method of the effective weight is: Where W is the effective weight of each parameter; P r is the score; P w is the theoretical weight; V is the vulnerability index; If the effective weight is greater than the theoretical weight, the contribution of the corresponding assessment factor to the vulnerability index is greater.

7. The vulnerability assessment method for groundwater nitrate contamination according to claim 1, It is characterized in that The DITAPH index was divided into four categories: low vulnerability, lower vulnerability, higher vulnerability and high vulnerability.

8. The vulnerability assessment method for groundwater nitrate contamination according to claim 1, It is characterized in that The method further comprises: The Pearson correlation coefficient was used to analyze the correlation between the measured groundwater nitrate concentration and the DITAPH index to verify the accuracy of the groundwater nitrate vulnerable zone NVZs map division.

9. The vulnerability assessment method for groundwater nitrate contamination according to claim 8, It is characterized in that The calculation method of the Pearson correlation coefficient is: Where R is the Pearson correlation coefficient; n is the data point, ρ is the nitrate concentration, in mg / L; DI is the DITAPH index; The R value ranges from -1 to 1, with 1 indicating a perfect positive correlation, -1 indicating a perfect negative correlation, and 0 indicating no linear relationship.

Images