CN117057088B - Software and method for simulating site pollutant cross-medium migration and accumulation process - Google Patents
Software and method for simulating site pollutant cross-medium migration and accumulation process Download PDFInfo
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- 238000013480 data collection Methods 0.000 claims abstract description 10
- 238000010206 sensitivity analysis Methods 0.000 claims abstract description 9
- 238000002360 preparation method Methods 0.000 claims abstract description 8
- 238000012216 screening Methods 0.000 claims abstract description 7
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Abstract
The invention discloses software and a method for simulating a site pollutant cross-medium migration and accumulation process, wherein the software comprises the following steps: a technical roadmap comprising data preparation, model simulation and inventory formulation, the data preparation comprising data collection and data processing, relating to the field of simulated site contaminant accumulation processes across media migration. The present invention summarizes a set of methods for processing data, running models, sensitivity analysis, uncertainty analysis, and result derivation, and integrates the methods and models into software. The software successfully solves the problem of data processing, integrates processing screening based on the existing data according to the perfection and sufficiency of different data, and is used for driving a model. After the model is finished, a report, a graph, a table and an area site pollutant emission list which are helpful for analysis are output. The model is expected to provide effective operation software for Chinese site investigation, site repair and site simulation.
Description
Technical Field
The invention relates to the field of simulating a site pollutant cross-medium migration and accumulation process, in particular to software and a method for simulating a site pollutant cross-medium migration and accumulation process.
Background
In recent years, soil physics modeling software has been increasingly used for modeling contaminant migration in soil and groundwater. Hydro has excellent simulation capability of soil hydrodynamic force and solute migration, but has some defects in the topical simulation combining the characteristics of Chinese sites (such as data, areas, parameters, etc.).
The existing scheme adopts the hydro to simulate, automatically processes input data, has strong professionality, has great difficulty in directly using software for simulation, and is time-consuming and labor-consuming. In particular, it is difficult for hydro to obtain some important parameters and inputs, such as the input of contaminants. Most of the various field-modulated data are text information, which needs to be digitized and has difficulty. Meanwhile, the simulation results are required to be used for evaluation analysis by adopting algorithms and software other than software.
Disclosure of Invention
The present invention is directed to a software and method for simulating a process of accumulation of site contaminants migrating across a medium, which solves the above-mentioned problems.
In order to achieve the above purpose, the present invention provides the following technical solutions:
software for simulating a site contaminant migration accumulation process across a medium, comprising: a technical roadmap comprising data preparation, model simulation and inventory formulation, the data preparation comprising data collection and data processing, the model simulation comprising model operation and result analysis, the data collection comprising site information, contaminant environment process parameters and output forms.
A method for simulating a site contaminant migration accumulation process across a medium, using the software described above, the data collection is as follows:
a first section, site information, the site information comprising:
the field regulation report acquires physical and chemical properties of the soil environment, land utilization history, soil pollution sources and soil environment quality;
collecting surface water, underground water, soil, atmosphere and vegetation samples in the field, and monitoring the concentration and range of pollutants; downloading or consulting the natural geographic information applied by the organization on line;
calculating an emission list by adopting an emission factor method according to the field industry industrial process, enterprise operation conditions and land utilization changes;
visit the field, and then sample and survey the field;
qualitatively judging the characteristic pollutants, determining a simulation target, adopting an excel form for input, and providing a shapefile for the data of the empty information;
the second part, the environmental process parameters of the pollutant, need to be obtained through experiments or quantitative relation for important parameters, comprises:
permeability coefficient: pumping experiments or earth pillar experiments;
porosity: earth pillar experiments and porosity measurement instruments;
soil particle size: sieving, sedimentation and laser;
dispersion degree: obtaining by dispersion experiment;
distribution coefficient: isothermal adsorption experiments; soil volume weight: a ring cutter method;
degradation coefficient: a laboratory controls the soil-loading column test;
rate coefficient: collecting a set of concentration-time data through experiments, and then calculating to obtain the concentration-time data;
other parameters: if a quantitative relation is established, part of site information is used as input data to obtain parameters of a second part, which are excel input;
and thirdly, setting iteration parameters, space-time resolution and output form according to the complexity of the target pollutant and the system, conceptualizing field information, quantifying the input and output of the system substances into boundary conditions of model input, digitizing field geographic information and land utilization information into a model system structure, and adjusting the spatial resolution and the time resolution of the model to be excel input.
Further, the data processing is as follows:
the method comprises the steps of searching data according to attributes by using codes, screening the data, removing repeated or deviated actual attribute information, and filling the first, second and third tables, wherein parameters which are necessary for the operation model are obtained, the model can be operated, parameters obtained by experience values are clicked and filled in for missing data, and 0 or experience values are adopted.
Further, the model was modeled as follows:
the processed data is input into a model through a Matlab script, a parameterization scheme of the pollutant environment process is realized by using hydro, and a simulation value of an observation point is output. By decisive coefficient R 2 To check the simulation effect of the model, the model performance R 2 If more than 0.6, the accumulated history can be reflected, otherwise, the input data needs to be adjusted, and the table interface is returned; the calculation formula is as follows:
wherein SST is the total square; SSR is regression square; the SSE is the sum of squares of the residuals,
sensitivity analysis is carried out by adopting the following formula, and the sensitivity coefficient C of model parameters S，i ：
C S，i ＝(Y 1，1，i -Y 1，0，i )/(0.1×Y 1，0，i ) (2)
C S，total ＝∑abs(C S，i ) (3)
Wherein C is S，i For the sensitivity coefficient of the model parameter in the medium i, Y 1，1，i And Y 1，0，i The concentration of the medium i when the parameter is 1.1 times and 1 time respectively; c (C) S，total As sensitivity coefficient C S，i Adding absolute values; in C S，total >0.5 is the standard, the parameters with obvious sensitivity are screened out,
analysis of model result uncertainty using Monte Carlo method, assuming parameters obeying normal distribution, randomly taking value C S，total >0.5 parameter, using Crystal Ball software to run 10000 times, calculating pollutant concentrations of different environment media at each observation pointThe coefficient of variation and the tetrad difference of the degree are calculated as follows:
c v ＝σ/μ (4)
Q＝C 3 -C 1 (5)
wherein C is v Is a variation coefficient, sigma is a standard deviation, and mu is an average value; q is a tetrad difference, C 3 For the upper quartile, C 1 Is the lower quartile.
Further, the list is formulated as follows:
using Matlab to process simulation data for extracting and calculating multi-medium flux of pollutants, manufacturing pollutant penetration curves, analyzing and evaluating pollutant accumulation concentration distribution of different time periods of different soil depths by adopting ArcGIS to manufacture grids; outputting a soil pollution list report, namely inputting pollutants which are emitted by different industries in multiple sources into soil through multiple ways, and calculating a pollution condition database through a soil pollution list function under the condition of cross-medium migration and multi-process accumulation in a certain period; the manifest generally contains a number of supporting data such as the spatiotemporal distribution of the networked contaminants, the migration flux of the individual environmental media, the model parametric history and fit results, model validation results, uncertainty analysis results.
Still further, the method for running the model comprises the following steps:
step S1: operating the hydro, creating a new project, filling information, and next;
step S2: setting a simulation range pattern;
step S3: setting an analog range and a gradient;
step S4: selecting a model simulation process and module;
step S5: setting time information;
step S6: setting output information;
step S7: setting an iteration standard;
step S8: selecting a soil hydraulic model;
step S9: setting water flow parameters;
step S10: solute transport model setting;
step S11: solute transport parameter settings;
step S12: setting a reactivity parameter;
step S13: setting time change boundary conditions;
step S14: space discretization setting;
step S15: default properties and grid information presentation;
step S16: setting soil types;
step S17: setting observation points;
step S18: initial water flow and concentration settings;
step S19: setting boundary conditions;
step S20: and (5) running the model.
Still further, the method of result analysis includes:
step W1: simulating the condition of pollutants;
step W2: sensitivity analysis;
step W3: uncertainty analysis;
step W4: the pollution list.
Compared with the prior art, the invention has the beneficial effects that:
the present invention summarizes a set of methods for processing data, running models, sensitivity analysis, uncertainty analysis, and result derivation, and integrates the methods and models into software. The software successfully solves the problem of data processing, integrates processing screening based on the existing data according to the perfection and sufficiency of different data, and is used for driving a model. After the model is finished, a report, a graph, a table and an area site pollutant emission list which are helpful for analysis are output. The model is expected to provide effective operation software for Chinese site investigation, site repair and site simulation.
Drawings
FIG. 1 is a technical roadmap of the invention;
FIG. 2 is a schematic diagram of a qualitative determination of a site contaminant input according to the present invention;
FIG. 3 is a schematic diagram of a set simulation range pattern of the present invention;
FIG. 4 is a schematic illustration of the setting of simulation ranges and gradients of the present invention;
FIG. 5 is a schematic diagram of the process and modules of the selection model simulation of the present invention;
FIG. 6 is a schematic diagram of a time information set of the present invention;
FIG. 7 is a schematic diagram of setting output information according to the present invention;
FIG. 8 is a schematic diagram of an iterative criteria setup of the present invention;
FIG. 9 is a schematic illustration of soil hydraulic model selection in accordance with the present invention;
FIG. 10 is a schematic diagram of a water flow parameter setting of the present invention;
FIG. 11 is a schematic diagram of a solute transport model setup of the present invention;
FIG. 12 is a schematic diagram of solute transport parameter settings of the present invention;
FIG. 13 is a schematic illustration of the reactive parameter set of the present invention;
FIG. 14 is a schematic diagram of a time-varying boundary condition setup of the present invention;
FIG. 15 is a schematic illustration of a spatially discretized arrangement of the present invention;
FIG. 16 is a schematic view of a soil type setting of the present invention;
FIG. 17 is a schematic view of an observation point arrangement of the present invention;
FIG. 18 is a schematic illustration of an initial water flow and concentration set-up of the present invention;
FIG. 19 is a schematic diagram of a boundary condition setup of the present invention;
FIG. 20 is a schematic diagram of a toolbar of the present invention;
FIG. 21 is a schematic view of the vertical distribution of dissolved contaminants (As) of the present invention;
FIG. 22 is a schematic view of the vertical distribution of contaminant (As) adsorption states of the present invention;
FIG. 23 is a schematic diagram of simulation results for site A of the present invention;
FIG. 24 is a schematic view of an experimental observation point of the present invention;
FIG. 25 is a schematic representation of a sensitivity assay of the present invention;
FIG. 26 is a schematic diagram of uncertainty intervals of the present invention;
fig. 27 is a schematic illustration of a 2019 site a soil arsenic pollution list of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-27, in an embodiment of the present invention, the present invention provides the following technical solutions: software and methods for simulating a site contaminant migration accumulation process across a medium, comprising: a technical roadmap comprising data preparation, model simulation and inventory formulation, the data preparation comprising data collection and data processing, the model simulation comprising model operation and result analysis, the data collection comprising site information, contaminant environment process parameters and output forms.
As a further scheme of the invention: the data collection (the design interface inputs data in the form of excel file and shapefile, if the space-time attribute is contained, the space-time information is needed to be contained) is as follows:
a first section, site information, the site information comprising:
the field regulation report acquires physical and chemical properties of the soil environment, land utilization history, soil pollution sources and soil environment quality;
collecting surface water, underground water, soil, atmosphere and vegetation samples in the field, and monitoring the concentration and range of pollutants; downloading or consulting the natural geographic information applied by the organization on line;
calculating an emission list by adopting an emission factor method according to the field industry industrial process, enterprise operation conditions and land utilization changes;
visit the field, and then sample and survey the field;
qualitatively judging the characteristic pollutants, determining a simulation target, adopting an excel form for input, and providing a shapefile for the data of the empty information;
the second part, the environmental process parameters of the pollutant, need to be obtained through experiments or quantitative relation for important parameters, comprises:
permeability coefficient: pumping experiments or earth pillar experiments;
porosity: earth pillar experiments and porosity measurement instruments;
soil particle size: sieving, sedimentation and laser;
dispersion degree: obtaining by dispersion experiment;
distribution coefficient: isothermal adsorption experiments; soil volume weight: a ring cutter method;
degradation coefficient: a laboratory controls the soil-loading column test;
rate coefficient: collecting a set of concentration-time data through experiments, and then calculating to obtain the concentration-time data;
other parameters: the method can be obtained by inversion and reference of documents, for example, a quantitative relation is established, part of site information can be used as input data to obtain parameters of a second part, and the parameters are excel input, but if experimental data such as time series data are encountered, the function of fitting according to different formulas is realized;
and thirdly, setting iteration parameters, space-time resolution and output form according to the complexity of the target pollutant and the system, conceptualizing field information, quantifying the input and output of the system substances into boundary conditions of model input, digitizing field geographic information and land utilization information into a model system structure, and adjusting the spatial resolution (1 m-100 m) and the time resolution (day-year) of the model to be excel input.
As a further scheme of the invention: the data processing (interface containing multiple tables, filling, screening and processing software for data input of varying sufficiency) is as follows:
the method comprises the steps of searching data according to attributes by using codes, screening the data, removing repeated or deviated actual attribute information, and filling in a first form, a second form and a third form, wherein the running model can be run by acquiring parameters necessary for the running model (the end is marked with A), the parameters which can be obtained by experience values (the end is marked with A), and for missing data, clicking and filling in, 0 or experience values (with a special database and callable) are adopted.
Processing shapefile, for example, fig. 2 is input position information of the pollutant, and dividing the input position information into dotted line and plane attributes, and extracting position information (coordinate point) of the pollutant input by using Matlab, and combining time variation of pollutant input amount of excel file to obtain pollutant input data with space-time information.
As a further scheme of the invention: the model was modeled as follows:
the processed data is input into a model through a Matlab script, a parameterization scheme (convection, dispersion, adsorption, degradation, volatilization and chemical processes) of the pollutant environment process is realized by using hydro, and a simulation value of an observation point (consistent with the observation position) is output. Based on the cross-medium observation data, the two time periods (calibration period and verification period) are set to use the deterministic coefficient (R 2 ) To check the simulation effect of the model, the model performance R 2 >0.6 can reflect the accumulated history, otherwise, the input data needs to be adjusted (returning to the form interface), and the simulation time end point is 2020. The calculation formula is as follows:
wherein SST is the total square; SSR is regression square; SSE is the sum of squares of the residuals.
According to the nothingThe policy and climate are set again, the design scenario simulates the future cumulative trend, and the simulation time end point is 2030. Sensitivity analysis is carried out by adopting the following formula, and the sensitivity coefficient C of model parameters S，i ：
C S，i ＝(Y 1，1，i -Y 1，0，i )/(0.1×Y 1，0，i ) (2)
C S，total ＝∑abs(C S，i ) (3)
Wherein C is S，i For the sensitivity coefficient of the model parameter in the medium i, Y 1，1，i And Y 1，0，i The concentration of the medium i when the parameter is 1.1 times and 1 time respectively; c (C) S，total As sensitivity coefficient C S，i Adding absolute values; in C S，total >And 0.5 is a standard, and the parameters with obvious sensitivity are screened out.
Analysis of model result uncertainty using Monte Carlo method, assuming parameters obeying normal distribution, randomly taking value C S，total >And (3) running 10000 times by using Crystal Ball software (which can be replaced by a simple algorithm) according to the parameter of 0.5, and calculating the variation coefficient and the quartile range of the pollutant concentrations of different environmental media at each observation point. The calculation formula is as follows:
C v ＝σ/μ (4)
Q＝C 3 -C 1 (5)
wherein C is V Is a variation coefficient, sigma is a standard deviation, and mu is an average value; q is a quartile difference (difference between upper quartile and lower quartile), C 3 For the upper quartile (i.e. at 75%), C 1 Lower quartile (i.e., at 25%).
As a further scheme of the invention: the list is formulated as follows:
the simulation data are processed by Matlab (the model automatically outputs simulation results) for extracting and calculating the multi-medium flux of the pollutants, making pollutant penetration curves and analyzing and evaluating. And (3) preparing pollutant accumulation concentration distribution of different soil depths and different time periods by adopting ArcGIS. And outputting a soil pollution list report, namely inputting pollutants which are emitted by different industries in multiple sources into soil through multiple ways, and calculating a pollution condition database through a soil pollution list function under the condition of cross-medium migration and multi-process accumulation in a certain period. The manifest generally contains a number of supportive data such as the spatiotemporal distribution of the networked contaminants (historical reconstruction and scene prediction), the migration flux of the individual environmental media, model tuning history and fitting results, model validation results, uncertainty analysis results.
As a further scheme of the invention: the method for running the model comprises the following steps:
step S1: operating the hydro, creating a new project (File-new), filling information, and next;
step S2: setting a simulation range style, selecting 2D-Simple and 2D-Vertical Plane XZ, selecting m units, and other defaults, next;
step S3: the simulation range and gradient were set, X was set to 20m, and y (depth) was set to 10m, which is the range of the severely contaminated area. The pollution below the depth of 10m is light and is not considered. Slope is 0, next;
step S4: selecting a model simulation process and module, and selecting a water flow model and a solute transport model (standard), next;
step S5: the time information is set, the time unit is year, the initial time is 0, the final time is 47 years, the initial time step is 0.01, and the minimum and maximum time steps are 0.001 and 5. Boundary conditions were noted 47 (one input per year), repeated 1;
step S6: setting output information, defaulting a printing option, defaulting a material balance partition, changing the printing quantity into 47, outputting one per year, clicking update and next;
step S7: setting iteration standard, setting the maximum iteration number as 10, checking the water content and the water head as 0.1 and 1, and inputting other parameters (obtained by parameter adjustment) as shown in fig. 8, wherein next is set;
step S8: selecting a soil hydraulic model, selecting a VG model, and hooking the model, wherein the subsequent hooking is required to be performed, and the air inlet value of clay is considered, and other defaults are shown in fig. 9 and next;
step S9: the water flow parameter setting adopts a set of parameters due to the nature type of the first layer of the filling layer and the second layer. Firstly, selecting 3 soil layers, clicking for updating, directly clicking on a soil parameter set of each row, selecting a left lower corner soil database catalog, selecting a soil type of drinking, directly obtaining parameters (improving the precision by adjusting parameters Ks later), and then, performing next;
step S10: solute transport model setup, space-time weight defaults, solute information, quantity 1, unit mg, frequency 38 years (year of contaminant input), other parameters defaults. The initial state adopts all concentrations and is hooked. Next;
step S11: the solute transport parameter is set, the volume weight and the horizontal and vertical dispersion coefficients are shown in figure 12, and the two parameters are set to 0. I.e. without taking into account unbalanced migration processes. Note that the unit is adjusted to kg/m 3 . The water diffusion coefficient is set to 1, the air diffusion coefficient is 0, next;
step S12: the reactivity parameter is set, except Kd and Alpha are set, the other parameters are set to zero, the adsorption is instantaneous equilibrium linear adsorption, each layer is required to be set with different Kd (parameter adjustment optimization in a range), alpha is set to 1 (transmission coefficient), and next is set;
step S13: setting time change boundary conditions, namely modifying pollutant input water fluxes Var.Fl1 and Var.Fl2 to be-10 and-1 (after parameter adjustment, the pollutant input and diffusion are mainly shown), cValue1 and cValue2 to be 15500 and 10000 (after parameter adjustment, within a reasonable range), and the time to be 1-38 (pollutant leakage) and 23-47 (landfill leachate) and next;
step S14: setting space discretization, X-axis discretization 100, Z-axis discretization 50, clicking update, other defaults, next;
step S15: displaying default attribute and grid information, and directly next;
step S16: soil type setting, clicking material on left side domain properties, clicking three soil types on right side, and drawing soil types in the middle soil. (finer soil types are performed due to severe contamination);
step S17: the observation point is set, observation nodes on the left side domain properties is clicked, insert observation nodes on the right side is clicked, and the observation point is added at the corresponding position in fig. 17;
step S18: initial water flow and concentration set, click Pressure Head on left initial condition, click set Pressure Head IC on right, frame all soil in the middle of fig. 18, set Head to-1, concentration set to 0, assume that the soil is clean and pollution-free;
step S19: boundary condition setting, clicking on the water flow on the left boundary conditions, clicking on the variable flow 1, variable flow 2 and free drain (free drain, direct downward fast migration, below ground water) clicked respectively, selecting the corresponding boundary in fig. 19. The boundary condition of the solute is consistent with the water flow, and no additional setting is needed;
step S20: the model is run, and the model is run by clicking on the toolbar, as shown in FIG. 20.
As a further scheme of the invention: the method for analyzing the results (word file, JPEG file and excel file) comprises the following steps:
step W1: the pollutant status simulation (JPEG file, excel file) as shown in fig. 21, shows that site a simulation results in pollution plume and concentration distribution in the most polluted region, which is mainly pollutant leakage, and waste residue accumulation/landfill is a secondary input. As shown in fig. 21 and 22, the pollutant not only has vertical migration, but also has lateral migration and adsorption effects on the cumulative distribution of the pollutant, as shown in fig. 23, which is a comparison of the actual measurement value and the simulation value of the simulation of the site a, the decisive coefficient is higher (R 2 >0.6). The calculation formula of the total soil pollution C (the air part of the soil is not considered) is as follows:
C＝ρ b c s +θc 1 (6)
wherein, c s Is the concentration of adsorbed solute; c l Is in dissolved state concentration; ρ b Soil volume weight; θ is the volume water content;
step W2: sensitivity analysis (JPEG file, excel file), wherein the deviation of ten parameters (tables) is +/-30%, and the average deviation value and deviation percentage of the simulation result are obtained by using experimental observation points as shown in FIG. 24;
the sensitivity analysis results are shown in FIG. 25;
step W3: uncertainty analysis (word file, JPEG file, excel file) according to uncertainty analysis algorithm, obtain uncertainty interval (JPEG file, excel file) and uncertainty analysis report (word file). The uncertainty interval is as follows in fig. 26;
uncertainty analysis report (field is written in advance and report word is output according to the sufficiency of data and the number of parameters adopting experience values): first, the model parameters are representative, and the soil moisture migration parameters come from default databases and documents and have a certain difference from actual site soil. And secondly, setting pollutant input. The method not only can be reversely solved through the existing model parameters and measured data, but also has no corresponding data for checking the space-time correctness of the input data, and has uncertainty. In addition, lower spatial-temporal resolution of the sampled data can introduce uncertainty. At the site scale, soil heterogeneity can significantly affect the results of model simulations. The simulation adopts higher vertical resolution except for the areas with serious pollution, and other areas adopt coarser resolution (insufficient data), so that uncertainty can be caused;
step W4: pollution list (JPEG file, excel file), use ArcGIS (Matlab also can do) to make the cumulative concentration distribution of pollutant of different soil depths of gridding different time periods (figure 27), for serious pollution area, take the dense grid (10 m), for lighter pollution area, sparse grid (30 m).
The foregoing description is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical solution of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (6)
1. A method for simulating a site contaminant migration accumulation process across a medium, characterized by: using software for simulating a site contaminant migration accumulation process across a medium, the software comprising: a technical roadmap comprising data preparation, model simulation and inventory formulation, the data preparation comprising data collection and data processing, the model simulation comprising model operation and result analysis, the data collection comprising site information, contaminant environment process parameters and output forms, the data collection being as follows:
a first section, site information, the site information comprising:
the field regulation report acquires physical and chemical properties of the soil environment, land utilization history, soil pollution sources and soil environment quality;
collecting surface water, underground water, soil, atmosphere and vegetation samples in the field, and monitoring the concentration and range of pollutants; downloading or consulting the natural geographic information applied by the organization on line;
calculating an emission list by adopting an emission factor method according to the field industry industrial process, enterprise operation conditions and land utilization changes;
visit the field, and then sample and survey the field;
qualitatively judging the characteristic pollutants, determining a simulation target, adopting an excel form for input, and providing a shapefile for the data of the empty information;
the second part, the environmental process parameters of the pollutant, need to be obtained through experiments or quantitative relation for important parameters, comprises:
permeability coefficient: pumping experiments or earth pillar experiments;
porosity: earth pillar experiments and porosity measurement instruments;
soil particle size: sieving, sedimentation and laser;
dispersion degree: obtaining by dispersion experiment;
distribution coefficient: isothermal adsorption experiments; soil volume weight: a ring cutter method;
degradation coefficient: a laboratory controls the soil-loading column test;
rate coefficient: collecting a set of concentration-time data through experiments, and then calculating to obtain the concentration-time data;
other parameters: if a quantitative relation is established, part of site information is used as input data to obtain parameters of a second part, which are excel input;
and thirdly, setting iteration parameters, space-time resolution and output form according to the complexity of the target pollutant and the system, conceptualizing field information, quantifying the input and output of the system substances into boundary conditions of model input, digitizing field geographic information and land utilization information into a model system structure, and adjusting the spatial resolution and the time resolution of the model to be excel input.
2. The method for simulating a site contaminant migration accumulation process across a medium according to claim 1, wherein: the data processing is as follows:
the method comprises the steps of searching data according to attributes by using codes, screening the data, removing repeated or deviated actual attribute information, and filling the first, second and third tables, wherein parameters which are necessary for the operation model are obtained, the model can be operated, parameters obtained by experience values are clicked and filled in for missing data, and 0 or experience values are adopted.
3. The method for simulating a site contaminant migration accumulation process across a medium according to claim 2, wherein: the model was modeled as follows:
the processed data is input into a model through a Matlab script, a parameterization scheme of the pollutant environment process is realized by using hydro, a simulation value of an observation point is output, and a decisive coefficient R is adopted 2 To check the simulation effect of the model, the model performance R 2 If the cumulative history is more than 0.6, otherwise, the input data needs to be adjusted, the table interface is returned, the simulation time end point is 2020, and the calculation formula is as follows:
wherein SST is the total square; SSR is regression square; SSE is the sum of squares of residuals;
sensitivity analysis is carried out by adopting the following formula, and the sensitivity coefficient C of model parameters S，i :
C S，i ＝(Y 1，1，i -Y 1，0，i )/(0.1×Y 1.0，i ) (2)
C S，total ＝∑abs(C S，i ) (3)
Wherein C is S，i For the sensitivity coefficient of the model parameter in the medium i, Y 1.1，i And Y 1.0，i The concentration of the medium i when the parameter is 1.1 times and 1 time respectively; c (C) S，total As sensitivity coefficient C S，i Adding absolute values; in C S，total Screening out parameters with obvious sensitivity by taking a value more than 0.5 as a standard;
analysis of model result uncertainty using Montecello method, assuming parameters obeying normal distribution, randomly taking value C S，total Parameters of more than 0.5 are operated 10000 times by using Crystal Ball software, and the variation coefficient and the tetrad difference of the pollutant concentration of different environment media at each observation point are calculated according to the following calculation formula:
C v ＝σ/μ (4)
Q＝C 3 -C 1 (5)
wherein C is v Is a variation coefficient, sigma is a standard deviation, and mu is an average value; q is a tetrad difference, c 3 For the upper quartile, C 1 Is the lower quartile.
4. A method for modeling a site contamination migration accumulation process across media according to claim 3, wherein the inventory is formulated as follows:
using Matlab to process simulation data for extracting and calculating multi-medium flux of pollutants, manufacturing pollutant penetration curves, analyzing and evaluating pollutant accumulation concentration distribution of different time periods of different soil depths by adopting ArcGIS to manufacture grids; outputting a soil pollution list report, namely inputting pollutants which are emitted by different industries in multiple sources into soil through multiple ways, and calculating a pollution condition database through a soil pollution list function under the condition of cross-medium migration and multi-process accumulation in a certain period; the manifest contains a number of supporting data, including in particular: the method comprises the steps of meshing pollutant space-time distribution, migration flux of each environment medium, model parameter adjustment history and fitting result, model verification result and uncertainty analysis result.
5. The method for modeling a site contamination migration accumulation process across a medium of claim 4, the method for model operation comprising:
step S1: operating the hydro, creating a new project, filling information, and next;
step S2: setting a simulation range pattern;
step S3: setting an analog range and a gradient;
step S4: selecting a model simulation process and module;
step S5: setting time information;
step S6: setting output information;
step S7: setting an iteration standard;
step S8: selecting a soil hydraulic model;
step S9: setting water flow parameters;
step S10: solute transport model setting;
step S11: solute transport parameter settings;
step S12: setting a reactivity parameter;
step S13: setting time change boundary conditions;
step S14: space discretization setting;
step S15: default properties and grid information presentation;
step S16: setting soil types;
step S17: setting observation points;
step S18: initial water flow and concentration settings;
step S19: setting boundary conditions;
step S20: and (5) running the model.
6. The method for simulating a site contaminant migration accumulation process across a medium according to claim 5, wherein: the result analysis method comprises the following steps:
step W1: simulating the condition of pollutants;
step W2: sensitivity analysis;
step W3: uncertainty analysis;
step W4: the pollution list.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106250666A (en) * | 2016-06-22 | 2016-12-21 | 中国水利水电科学研究院 | A kind of irrigation system ecumene lake nitrogen and phosphorus loading analogy method |
| CN110729026A (en) * | 2019-10-28 | 2020-01-24 | 中国科学院生态环境研究中心 | Polychlorinated biphenyl space-time quantitative tracing method based on combination of mixed list construction and space multi-medium model simulation |
| CN110991054A (en) * | 2019-12-06 | 2020-04-10 | 暨南大学 | Method for simulating regression and trend distribution of space-time migration of organic pollutants |
| CN112434076A (en) * | 2020-10-28 | 2021-03-02 | 南京润江安全环保科技有限公司 | Soil pollutant migration and early warning simulation method and system |
| CN112507048A (en) * | 2020-11-11 | 2021-03-16 | 中国地质调查局水文地质环境地质调查中心 | Polluted site water and soil environment multi-element one-stop management system |
| WO2021208393A1 (en) * | 2020-04-15 | 2021-10-21 | 北京工业大学 | Inversion estimation method for air pollutant emission inventory |
| KR102379326B1 (en) * | 2021-09-03 | 2022-03-30 | 대한민국 | Disaster investigation system based on special vehicle and disaster investigation method using the same |
| CN114417604A (en) * | 2022-01-18 | 2022-04-29 | 中国科学院生态环境研究中心 | Soil heavy metal accumulation process probability simulation method based on mass balance principle |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11631022B2 (en) * | 2018-03-29 | 2023-04-18 | Daybreak, Llc | Forecasting soil and groundwater contamination migration |
-
2023
- 2023-06-27 CN CN202310764416.XA patent/CN117057088B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106250666A (en) * | 2016-06-22 | 2016-12-21 | 中国水利水电科学研究院 | A kind of irrigation system ecumene lake nitrogen and phosphorus loading analogy method |
| CN110729026A (en) * | 2019-10-28 | 2020-01-24 | 中国科学院生态环境研究中心 | Polychlorinated biphenyl space-time quantitative tracing method based on combination of mixed list construction and space multi-medium model simulation |
| CN110991054A (en) * | 2019-12-06 | 2020-04-10 | 暨南大学 | Method for simulating regression and trend distribution of space-time migration of organic pollutants |
| WO2021208393A1 (en) * | 2020-04-15 | 2021-10-21 | 北京工业大学 | Inversion estimation method for air pollutant emission inventory |
| CN112434076A (en) * | 2020-10-28 | 2021-03-02 | 南京润江安全环保科技有限公司 | Soil pollutant migration and early warning simulation method and system |
| CN112507048A (en) * | 2020-11-11 | 2021-03-16 | 中国地质调查局水文地质环境地质调查中心 | Polluted site water and soil environment multi-element one-stop management system |
| KR102379326B1 (en) * | 2021-09-03 | 2022-03-30 | 대한민국 | Disaster investigation system based on special vehicle and disaster investigation method using the same |
| CN114417604A (en) * | 2022-01-18 | 2022-04-29 | 中国科学院生态环境研究中心 | Soil heavy metal accumulation process probability simulation method based on mass balance principle |
Non-Patent Citations (2)
| Title |
|---|
| 包气带污染物运移过程基于Hydrus-1D的参数敏感性分析;陈铭;韩明;黄双;王晶玮;袁立江;王会义;邵峰;徐耀红;;电力勘测设计;20180731(S1);6-10 * |
| 地下水燃油污染物迁移模型的参数敏感性分析;张洪伟等;兰州交通大学学报;20181015;第37卷(第5期);74-79 * |
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