A numerical prediction method and system for the evolution of heavy metal pollution load in a watershed

Abstract

The present invention discloses a numerical prediction method and system for the evolution of heavy metal pollution load in a watershed, and belongs to the technical field of heavy metal pollution prevention in a watershed. Existing watershed pollution prediction schemes do not take into account the influence of heavy metal pollution leaching from the soil due to rainfall and the sedimentation influence of atmospheric heavy metal pollution, resulting in the inability to accurately simulate the transformation and transport process of heavy metal pollution. The present invention provides a numerical prediction method for the evolution of heavy metal pollution load in a watershed, which obtains heavy metal multidimensional evolution data by constructing a heavy metal parameter analysis model, a heavy metal three-dimensional evolution model, and a heavy metal coupling prediction model; and then couples the heavy metal multidimensional evolution data with weather data and hydrological calculation data to obtain accurate heavy metal pollution prediction values, thereby accurately simulating the evolution process of heavy metal pollution between water, land, and air, and further more comprehensively tracking and predicting the development trend of heavy metal pollution load in a watershed.

Description

Technical Field

[0001] The present invention relates to a numerical prediction method and system for the evolution of heavy metal pollution load in a watershed, belonging to the technical field of watershed heavy metal pollution prevention. Background Art

[0002] The current means of preventing and controlling heavy metal pollution in river basin waters mainly relies on data monitoring, which has a certain lag and cannot provide an intuitive reference for the future development trend of heavy metal pollution loads.

[0003] Chinese literature (Liu Kejia. Application of improved SWAT model in simulation of antimony pollution load in soil-water interface flow in antimony mining area [D]. Hunan University of Science and Technology, 2015.) conducted an on-site investigation of the characteristics of the study area environment, then formulated a sampling plan for the study area, and constructed a SWAT model to consider the vertical and lateral diffusion of heavy metals in soil-water interface flow, and constructed a two-dimensional or three-dimensional migration and transformation model to improve the accuracy of the transformation mechanism. Finally, the model parameters were optimized to simulate the pollution load of heavy metal antimony in the soil-water interface of the antimony mining area, providing a theoretical basis for the assessment and prevention of antimony pollution in the study area.

[0004] Although the above scheme takes into account the exchange of heavy metal pollution at the water-soil interface, it does not take into account the impact of heavy metals in terrestrial soil and atmospheric heavy metal pollution on the migration of watersheds. It is unable to fully simulate the transformation and transport process of heavy metal pollution, resulting in difficulty in fully calculating the impact of heavy metal pollution loads in actual calculations. Therefore, the existing scheme cannot accurately simulate the transformation and transport process of heavy metal pollution, and cannot accurately predict the changes in heavy metal pollution loads, which is not conducive to the prevention and management of heavy metal pollution in watershed waters.

[0005] The information disclosed in this Background Art is only for understanding the background of the present inventive concept and therefore it may include information that does not constitute prior art. Summary of the Invention

[0006] In response to the above problem or one of the above problems, the first object of the present invention is to provide a numerical prediction method and system for the evolution of heavy metal pollution load in a watershed, which fully considers the migration and transformation laws of heavy metal pollution between water bodies, land soil, and air, and obtains heavy metal transformation property parameters and heavy metal multidimensional evolution data between water, land, and air by constructing a heavy metal pollution collection model, a heavy metal parameter analysis model, a heavy metal three-dimensional evolution model, and a heavy metal coupling prediction model; then the heavy metal multidimensional evolution data is coupled with weather data and hydrological calculation data to obtain data such as the amount of heavy metal leached from the soil due to rainfall, the heavy metal load value of atmospheric deposition to the soil and water bodies, and then, combined with the emission of heavy metal pollution point sources, the transformation and transport process of heavy metal pollution is accurately simulated, so that accurate heavy metal pollution prediction values ​​can be obtained, which is beneficial to the prevention and management of heavy metal pollution in watershed waters, and is suitable for tracking and simulating heavy metal pollution loads in watersheds.

[0007] In response to the above problem or one of the above problems, the second purpose of the present invention is to provide a numerical prediction method and system for the evolution of heavy metal pollution load in a river basin, which fully considers the exchange characteristics of heavy metal pollution at the water, land and air interface, and accurately simulates the evolution process of heavy metal pollution between water, land and air based on weather changes and hydrological calculations, so as to comprehensively perform numerical simulation on the temporal and spatial distribution of heavy metal pollution load in the river basin, and thus can more comprehensively track and predict the development trend of heavy metal pollution load in the river basin.

[0008] To achieve one of the above purposes, the first technical solution of the present invention is:

[0009] A numerical prediction method for the evolution of heavy metal pollution loads in a watershed includes the following:

[0010] Through the pre-built heavy metal pollution collection model, collect the water, land and air heavy metal pollution data in the basin to be predicted;

[0011] Using the pre-built heavy metal parameter analysis model, the water, land and air heavy metal pollution data are processed to obtain the heavy metal transformation property parameters;

[0012] Using a pre-built three-dimensional heavy metal evolution model and based on heavy metal transformation parameters, we simulated the leaching of heavy metals from soil due to rainfall, the atmospheric deposition of heavy metals, and the changes in heavy metal loads in water bodies. This generated multi-dimensional heavy metal evolution data, which was used to characterize the migration and changes of heavy metals between land, water, and air.

[0013] Using a pre-built heavy metal coupling prediction model, the multi-dimensional evolution data of heavy metals are coupled with weather data and hydrological calculation data to calculate the evolution process of heavy metal pollution between water, land and air, and obtain the predicted value of heavy metal pollution.

[0014] The present invention fully considers the migration and transformation laws of heavy metal pollution between water bodies, land soil, and air, and obtains heavy metal transformation property parameters and heavy metal multidimensional evolution data between water, land, and air by constructing a heavy metal pollution collection model, a heavy metal parameter analysis model, a heavy metal three-dimensional evolution model, and a heavy metal coupling prediction model; then the heavy metal multidimensional evolution data is coupled with weather data and hydrological calculation data to obtain data such as the amount of heavy metal leached from the soil due to rainfall, the heavy metal load value deposited by the atmosphere to the soil and water bodies, and then, combined with the emission of heavy metal pollution point sources, the transformation and transport process of heavy metal pollution is accurately simulated, thereby obtaining accurate heavy metal pollution prediction values, which is beneficial to the prevention and management of heavy metal pollution in watershed waters.

[0015] Furthermore, the present invention fully considers the exchange characteristics of heavy metal pollution at the interface between water, land and air, and accurately simulates the evolution process of heavy metal pollution between water, land and air based on weather changes and hydrological calculations, so that the temporal and spatial distribution of heavy metal pollution loads in the basin can be comprehensively numerically simulated, and thus the development trend of heavy metal pollution loads in the basin can be more comprehensively tracked and predicted.

[0016] As preferred technical measures:

[0017] The method for collecting water, land, and air heavy metal pollution data within the basin to be predicted using the pre-built heavy metal pollution collection model is as follows:

[0018] Obtain the location information of the watershed to be predicted;

[0019] Based on the location information of the watershed to be predicted, collect point source emission data of heavy metal pollution in the watershed to be predicted;

[0020] Point source emission data shall at least include the location of the point source, watershed runoff, watershed sediment load, and heavy metal load;

[0021] According to the point source emission data, a point source emission database is constructed based on the daily load constant method;

[0022] Based on the location information of the watershed to be predicted, collect data on heavy metal pollution content in the air and soil of the watershed;

[0023] Heavy metal pollution data include the monthly average soil heavy metal load and the monthly average atmospheric heavy metal load in the basin;

[0024] Based on the heavy metal pollution content data and the monthly average load constant method, an air and land pollution database was constructed;

[0025] The point source emission database and the air and land pollution database are aggregated to form the water, land and air heavy metal pollution data, which are used as the heavy metal load input for numerical calculations.

[0026] As preferred technical measures:

[0027] The method for processing the water, land, and air heavy metal pollution data using the pre-built heavy metal parameter analysis model to obtain the heavy metal transformation property parameters is as follows:

[0028] Based on the heavy metal pollution data on land, water and air, obtain the types of heavy metals, soil types, longitudinal diffusion coefficients of heavy metals, calculated adsorption coefficients, and distribution coefficients between sediment and water, as well as dry and wet conditions;

[0029] Determine the desorption coefficient of heavy metals and the distribution coefficient of heavy metals between suspended matter and water based on the type of heavy metals, the longitudinal diffusion coefficient of heavy metals, the measured adsorption coefficient and the distribution coefficient between sediment and water;

[0030] The comprehensive sedimentation velocity, comprehensive sedimentation effect constant and resuspension coefficient of heavy metals are calculated using the desorption coefficient of heavy metals and the distribution coefficient of heavy metals in suspended matter and water.

[0031] Determine soil heavy metal content and pesticide and fertilizer usage information based on the type of heavy metals, soil type, and pesticide and fertilizer usage regulations;

[0032] The types of heavy metals, soil types, longitudinal diffusion coefficients of heavy metals, measured adsorption coefficients and distribution coefficients between sediment and water and dry and wet conditions, desorption coefficients of heavy metals, distribution coefficients of heavy metals in suspended matter and water bodies, comprehensive sedimentation velocity of heavy metals, comprehensive constants affecting sedimentation, resuspension coefficients, equation parameters, soil heavy metal content, and information on the use of pesticides and fertilizers were summarized to obtain the parameters of heavy metal transformation properties.

[0033] As preferred technical measures:

[0034] Using the pre-built three-dimensional evolution model of heavy metals, the method for simulating the leaching of heavy metals from soil due to rainfall based on the parameters of heavy metal transformation properties is as follows:

[0035] Based on the parameters of heavy metal transformation properties, obtain the soil heavy metal content and the use of pesticides and fertilizers;

[0036] Based on the soil heavy metal content, pesticide and fertilizer usage information, equivalent rainfall duration, and multiple unknown variable parameters, a heavy metal rainfall leaching equation was constructed.

[0037] The heavy metal rainfall leaching equation was used to fit the soil heavy metal leaching data under different rainwater pH and multiple rainfall durations, and the fitting results were obtained.

[0038] According to the fitting results, the values ​​of variable parameters under different rainwater pH values ​​are determined;

[0039] Summarize the variable parameter values ​​of different rainwater pH values, and then use the exponential function to fit them to obtain the fitting function of the variable with respect to pH value;

[0040] The fitting function of the variable related to pH is substituted into the heavy metal rainfall leaching equation to form a calculation formula for the heavy metal leaching amount related to rainfall duration and rainwater pH, thereby simulating the leaching process of heavy metals from the soil due to rainfall.

[0041] As preferred technical measures:

[0042] The method for simulating the atmospheric heavy metal deposition process is as follows:

[0043] Determine the type of heavy metals, soil type, and dry and wet conditions based on the parameters of heavy metal transformation properties;

[0044] Determine heavy metal deposition information based on heavy metal types, soil types, and dry and wet conditions;

[0045] Heavy metal deposition information includes wet deposition heavy metal content, dry deposition heavy metal content, wet deposition rate, and dry deposition rate;

[0046] Based on rainfall conditions and air pressure information, obtain actual air pressure and reference air pressure;

[0047] The ratio of the actual air pressure to the reference air pressure is used as the air pressure factor;

[0048] Based on rainfall conditions and average wind speed information, obtain reference average wind speed and actual average wind speed;

[0049] The ratio of the reference average wind speed to the actual average wind speed is used as the wind speed factor;

[0050] Based on the heavy metal deposition information, air pressure factors, and wind speed factors, the calculation formulas for the wet and dry deposition fluxes of heavy metals were constructed.

[0051] The calculation formulas for the wet deposition flux and the dry deposition flux of heavy metals are jointly solved to obtain the load of heavy metals deposited from the atmosphere to the soil and water bodies, thereby simulating the atmospheric heavy metal deposition process.

[0052] Furthermore, using the pre-built three-dimensional evolution model of heavy metals, the method for simulating the change process of heavy metal load in water bodies based on the parameters of heavy metal transformation properties is as follows:

[0053] Collect meteorological data from weather stations within the basin, including annual maximum wind speed, daily maximum rainfall, and monthly rainfall observations;

[0054] Calculate the soil moisture and precipitation in a certain water area based on the annual maximum wind speed, daily maximum rainfall and monthly rainfall observations;

[0055] Based on the soil moisture and precipitation of a certain water area, the hydrological calculation data is calculated using a pre-built hydrological calculation model; the hydrological calculation data at least includes soil moisture content, watershed flow velocity, flow cross-sectional area and watershed depth;

[0056] Determine the mass concentration of dissolved heavy metals and the mass concentration of suspended heavy metals based on heavy metal transformation parameters, hydrological calculation data, and heavy metal pollution data on land, water, and air;

[0057] The heavy metal evolution equation is constructed based on the mass concentration of dissolved heavy metals, the mass concentration of suspended heavy metals, the water depth, the longitudinal component of the water flow velocity and the average flow velocity of the water section.

[0058] Set the initial heavy metal concentration at the beginning of the watershed and the boundary conditions of heavy metal concentration at the watershed boundary;

[0059] The boundary condition of heavy metal concentration is the time series of heavy metal concentration;

[0060] According to the initial concentration of heavy metals, the boundary conditions of heavy metal concentrations, the grid size and the time step, the heavy metal evolution equation is discretized using the implicit difference method to obtain the implicit difference expression of heavy metal concentration, which is used to represent the heavy metal mass concentration of the watershed node to be predicted at a certain moment.

[0061] Based on the convection-diffusion characteristics, the implicit differential expression of heavy metal concentration is transformed to obtain the conversion prediction calculation equation group for calculating the heavy metal mass concentration;

[0062] By superimposing solutes, the mass concentration source terms of dissolved heavy metals and the mass concentration source terms of suspended heavy metals are merged into the transformation prediction calculation equations to construct the overall prediction calculation equations, so that the mass concentrations of point source and non-point source heavy metals can be considered simultaneously in the calculation process.

[0063] The overall prediction calculation equations are written as a tridiagonal matrix and solved using the pursuit method to obtain the mass concentration of heavy metals in each phase at each watershed node at each moment.

[0064] The heavy metal mass concentration values ​​of each phase at several watershed nodes at multiple times are summarized to obtain the heavy metal load information of the watershed, which is used to characterize the distribution evolution and component transformation process of the heavy metal pollution load in the watershed, so as to simulate the change process of the heavy metal load of the watershed.

[0065] As preferred technical measures:

[0066] It also includes using a pre-built three-dimensional evolution model of heavy metals to simulate the biological reduction process of heavy metals based on the parameters of heavy metal transformation properties. The method is as follows:

[0067] Determine the vegetation cover type based on the soil type and the geographical location of the watershed to be predicted;

[0068] According to the vegetation cover type and heavy metal transformation parameters, the absorption ratio of soil heavy metals by organisms and the filtration reduction ratio of atmospheric heavy metal deposition by organisms were obtained.

[0069] According to the absorption ratio and filtration reduction ratio, the biological reduction amount of heavy metals is determined to achieve the simulation of the heavy metal reduction process.

[0070] As preferred technical measures:

[0071] The method for obtaining the predicted value of heavy metal pollution is as follows:

[0072] Substitute the rainfall data of the basin to be predicted into the calculation formula of heavy metal leaching amount related to rainfall duration and rainwater pH to obtain the heavy metal leaching amount of the basin to be predicted;

[0073] According to the atmospheric heavy metal deposition process, the calculation formulas for the wet deposition flux and the dry deposition flux of heavy metals are determined;

[0074] Based on the meteorological information and area of ​​the basin to be predicted, and combined with the calculation formulas for wet deposition flux and dry deposition flux of heavy metals, the deposition load value of heavy metals from the atmosphere to the soil and water bodies is calculated;

[0075] Use point source emission data of heavy metals as new land, water and air heavy metal pollution data;

[0076] Substitute the new land, water, and air heavy metal pollution data and hydrological calculation data into the process of heavy metal load changes in water bodies, and by superimposing solutes, merge the mass concentration source terms of dissolved heavy metals and the mass concentration source terms of suspended heavy metals into the transformation prediction calculation equations to construct the overall prediction calculation equations.

[0077] The overall prediction calculation equation group is solved to obtain the heavy metal mass concentration at each moment in the basin, that is, the heavy metal pollution prediction value, which is used to characterize the distribution evolution and component transformation process of heavy metal pollution load in water bodies.

[0078] Furthermore, rainfall data includes rainfall duration and rainwater pH. Meteorological information includes rainfall conditions, actual air pressure, and actual average wind speed. Heavy metal point source emission data includes point source emission data for heavy metal leaching, point source emission data for sedimentation load, and point source emission data for heavy metal pollution.

[0079] Furthermore, the calculation method for determining the amount of heavy metal leaching in relation to rainfall duration and rainwater pH is as follows:

[0080] Based on the multidimensional evolution data of heavy metals, the process of heavy metal leaching from soil due to rainfall, the process of heavy metal deposition in the atmosphere and the change process of heavy metal load in water bodies were determined;

[0081] Collect meteorological data from meteorological stations within the basin, including rainfall duration, rainwater pH, actual air pressure, actual average wind speed, annual maximum wind speed, daily maximum rainfall, and monthly rainfall observation values.

[0082] Calculate the soil moisture and precipitation of the basin to be predicted based on the annual maximum wind speed, daily maximum rainfall and monthly rainfall observations;

[0083] Based on the soil moisture and precipitation of the watershed to be predicted, the hydrological calculation data are calculated using a pre-built hydrological calculation model; the hydrological calculation data at least includes soil moisture content, watershed flow velocity, flow cross-sectional area and watershed depth;

[0084] Based on the process of heavy metals leaching from the soil due to rainfall, the calculation formula for the amount of heavy metal leaching related to rainfall duration and rainwater pH was determined.

[0085] As preferred technical measures:

[0086] The method of constructing the hydrological calculation model is as follows:

[0087] Collect land use classification data of the watershed to be predicted;

[0088] Obtain soil type distribution information and soil attribute data based on land use classification data;

[0089] Obtain several sub-basins of the basin to be predicted, and subdivide the sub-basins according to soil type distribution information and soil attribute data, and superimpose the soil type distribution information and soil attribute data to obtain several hydrological calculation units;

[0090] Each hydrological calculation unit has a single land use type and soil type, and a hydrological variable matrix is ​​established on each hydrological calculation unit;

[0091] According to the water area information, several river calculation units are constructed, and a river runoff variable matrix is ​​set on each river calculation unit for river evolution calculation and heavy metal load transmission calculation;

[0092] Several hydrological calculation units and river calculation units are coupled to obtain a hydrological calculation model, which serves as a carrier for calculating water balance and material transport.

[0093] Furthermore, land use classification data includes information on cultivated land, forest land, pasture, industrial land, residential land, water areas, and pesticide and fertilizer use. Soil attribute data includes soil layer structure, available moisture content, saturated hydraulic conductivity, soil wet density, soil erodibility factor, and the types and contents of heavy metals in the soil. The hydrological variable matrix, used to store hydrological calculation variables, includes soil moisture content, rainfall, surface runoff, evaporation, infiltration, groundwater runoff, and heavy metal concentrations. The river runoff variable matrix includes river runoff volume, river water volume, and heavy metal concentrations.

[0094] Furthermore, based on the soil moisture and precipitation of a certain water area, the method for calculating the hydrological calculation data using the pre-built hydrological calculation model is as follows:

[0095] Obtain soil moisture and precipitation in a water area, and set the initial hydrological conditions of the watershed;

[0096] The initial hydrological conditions include runoff, evaporation, infiltration and groundwater runoff;

[0097] Soil moisture, precipitation and initial hydrological conditions are input into the hydrological calculation model for hydrological simulation. Based on the principle of water balance, the changes in runoff water volume in the basin surface, rivers, soil and groundwater are simulated to achieve water balance between hydrological calculation units, thereby obtaining hydrological calculation data; the hydrological calculation data at least includes soil moisture content, basin flow velocity, flow cross-sectional area and basin water depth.

[0098] As preferred technical measures:

[0099] The method to obtain several sub-basins of the basin to be predicted is as follows:

[0100] Obtain the location information of the watershed to be predicted;

[0101] Based on the location information of the watershed to be predicted, digital elevation data of the watershed to be predicted is obtained;

[0102] Based on the digital elevation data of the watershed to be predicted, the boundary location information with a slope greater than 10% is obtained;

[0103] Determine the boundaries of several sub-basins through boundary location information;

[0104] Determine the sub-basin range based on the sub-basin boundary and basin area threshold;

[0105] According to the scope of each sub-basin, the outlet of each sub-basin is determined, so that the entire basin is divided into several sub-basins that conform to the basin's geographical characteristics and natural runoff characteristics.

[0106] Furthermore, the method of inputting soil moisture, precipitation and hydrological initial conditions into the hydrological calculation model for hydrological simulation is as follows:

[0107] According to soil moisture, precipitation and initial hydrological conditions, surface runoff and infiltration are calculated based on the surface runoff curve method;

[0108] Based on the surface runoff and infiltration, the soil moisture content at a certain moment is calculated using the water transport formula;

[0109] Calculate the flow velocity of the river channel using the Manning formula and based on the hydraulic radius of the section, the slope and roughness of the river channel;

[0110] Calculate the cross-sectional area of ​​the flow according to the river water volume, surface runoff and time step;

[0111] Then, the river depth is calculated based on the cross-sectional area, river bottom width, and river channel slope;

[0112] The soil moisture content, watershed flow velocity, flow cross-sectional area and watershed water depth are summarized to obtain hydrological calculation data.

[0113] To achieve one of the above purposes, the second technical solution of the present invention is:

[0114] A numerical prediction method for the evolution of heavy metal pollution loads in a watershed includes the following:

[0115] Through the pre-built heavy metal pollution collection model, collect the water, land and air heavy metal pollution data in the basin to be predicted;

[0116] Using the pre-built heavy metal parameter analysis model, the water, land and air heavy metal pollution data are processed to obtain the heavy metal transformation property parameters;

[0117] Using a pre-built three-dimensional evolution model of heavy metals, based on the parameters of heavy metal transformation properties, the process of heavy metal leaching from soil due to rainfall, the process of heavy metal deposition in the atmosphere, the process of heavy metal deduction and reduction by organisms, and the process of heavy metal load changes in water bodies were simulated. Multi-dimensional evolution data of heavy metals were obtained to characterize the migration changes of heavy metals between water, land, air and organisms.

[0118] Using a pre-built heavy metal coupling prediction model, the multi-dimensional evolution data of heavy metals are coupled with weather data and hydrological calculation data to obtain the amount of heavy metal leaching from the soil due to rainfall, the heavy metal load value of atmospheric deposition to the soil and water bodies, and the deduction reduction of heavy metals in the soil and heavy metal deposition by organisms. Then, combined with the emissions from point sources of heavy metal pollution, the predicted value of heavy metal pollution is calculated to comprehensively calculate the evolution process of heavy metal pollution between water, land, air and life.

[0119] The present invention fully considers the migration and transformation laws of heavy metal pollution between water bodies, land soil, air and organisms, and obtains heavy metal transformation property parameters and heavy metal multidimensional evolution data between water, land, air and organisms by constructing a heavy metal pollution collection model, a heavy metal parameter analysis model, a heavy metal three-dimensional evolution model and a heavy metal coupling prediction model; then the heavy metal multidimensional evolution data is coupled with weather data and hydrological calculation data to obtain data such as the amount of heavy metal leached from the soil due to rainfall, the heavy metal load value of atmospheric deposition to the soil and water bodies, and the deduction and reduction of heavy metals in the soil and heavy metal deposition by organisms. Then, combined with the emission of heavy metal pollution point sources, the transformation and transport process of heavy metal pollution is accurately simulated, thereby obtaining accurate heavy metal pollution prediction values, which is beneficial to the prevention and management of heavy metal pollution in watershed waters, and thus can more comprehensively track and predict the development trend of heavy metal pollution load in the basin.

[0120] To achieve one of the above purposes, the third technical solution of the present invention is:

[0121] A numerical prediction system for the evolution of heavy metal pollution load in a watershed, comprising:

[0122] one or more processors;

[0123] a storage device for storing one or more programs;

[0124] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned numerical prediction method for the evolution of heavy metal pollution load in a watershed.

[0125] To achieve one of the above purposes, the second technical solution of the present invention is:

[0126] A numerical prediction system for the evolution of heavy metal pollution load in a watershed, comprising:

[0127] one or more processors;

[0128] a storage device for storing one or more programs;

[0129] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned numerical prediction method for the evolution of heavy metal pollution load in a watershed.

[0130] Compared with the existing technical solutions, the present invention has the following beneficial effects:

[0131] The present invention fully considers the migration and transformation laws of heavy metal pollution between water bodies, land soil, and air, and obtains heavy metal transformation property parameters and heavy metal multidimensional evolution data between water, land, and air by constructing a heavy metal pollution collection model, a heavy metal parameter analysis model, a heavy metal three-dimensional evolution model, and a heavy metal coupling prediction model; then the heavy metal multidimensional evolution data is coupled with weather data and hydrological calculation data to obtain data such as the amount of heavy metal leached from the soil due to rainfall, the heavy metal load value deposited by the atmosphere to the soil and water bodies, and then, combined with the emission of heavy metal pollution point sources, the transformation and transport process of heavy metal pollution is accurately simulated, thereby obtaining accurate heavy metal pollution prediction values, which is beneficial to the prevention and management of heavy metal pollution in watershed waters.

[0132] Furthermore, the present invention fully considers the exchange characteristics of heavy metal pollution at the interface between water, land, air and organisms, and accurately simulates the evolution process of heavy metal pollution between water, land, air and organisms based on weather changes and hydrological calculations, so that the temporal and spatial distribution of heavy metal pollution loads in the basin can be comprehensively numerically simulated, and thus the development trend of heavy metal pollution loads in the basin can be more comprehensively tracked and predicted. BRIEF DESCRIPTION OF THE DRAWINGS

[0133] Figure 1 This is a schematic diagram of the first flow chart of the numerical prediction method for the evolution of heavy metal pollution load in a watershed according to the present invention;

[0134] Figure 2 This is a second flow chart of the numerical prediction method for the evolution of heavy metal pollution load in a watershed according to the present invention;

[0135] Figure 3 The figure is a schematic diagram of the changes in heavy metal mass concentration in a certain river basin obtained by applying the present invention. DETAILED DESCRIPTION

[0136] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0137] Rather, the present invention encompasses any alternatives, modifications, equivalents, and solutions that fall within the spirit and scope of the present invention as defined by the claims. Furthermore, to facilitate a better understanding of the present invention, certain specific details are described in detail below in the detailed description of the present invention. Those skilled in the art will be able to fully understand the present invention without these details.

[0138] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention pertains. The terms used herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention.

[0139] like Figure 1 As shown, the first specific embodiment of the numerical prediction method for the evolution of heavy metal pollution load in a watershed of the present invention is as follows:

[0140] A numerical prediction method for the evolution of heavy metal pollution loads in a watershed includes the following:

[0141] Through the pre-built heavy metal pollution collection model, collect the water, land and air heavy metal pollution data in the basin to be predicted;

[0142] Using the pre-built heavy metal parameter analysis model, the water, land and air heavy metal pollution data are processed to obtain the heavy metal transformation property parameters;

[0143] Using a pre-built three-dimensional heavy metal evolution model and based on heavy metal transformation parameters, we simulated the leaching of heavy metals from soil due to rainfall, the atmospheric deposition of heavy metals, and the changes in heavy metal loads in water bodies. This generated multi-dimensional heavy metal evolution data, which was used to characterize the migration and changes of heavy metals between land, water, and air.

[0144] Using a pre-built heavy metal coupling prediction model, the multi-dimensional evolution data of heavy metals are coupled with weather data and hydrological calculation data to calculate the evolution process of heavy metal pollution between water, land and air, and obtain the predicted value of heavy metal pollution.

[0145] The second specific embodiment of the numerical prediction method of the heavy metal pollution load evolution in the watershed of the present invention is as follows:

[0146] A numerical prediction method for the evolution of heavy metal pollution loads in a watershed includes the following:

[0147] Through the pre-built heavy metal pollution collection model, collect the water, land and air heavy metal pollution data in the basin to be predicted;

[0148] Using the pre-built heavy metal parameter analysis model, the water, land and air heavy metal pollution data are processed to obtain the heavy metal transformation property parameters;

[0149] Using a pre-built three-dimensional evolution model of heavy metals, based on the parameters of heavy metal transformation properties, the process of heavy metal leaching from soil due to rainfall, the process of heavy metal deposition in the atmosphere, the process of heavy metal deduction and reduction by organisms, and the process of heavy metal load changes in water bodies were simulated. Multi-dimensional evolution data of heavy metals were obtained to characterize the migration changes of heavy metals between water, land, air and organisms.

[0150] Using a pre-built heavy metal coupling prediction model, the multi-dimensional evolution data of heavy metals are coupled with weather data and hydrological calculation data to obtain the amount of heavy metal leaching from the soil due to rainfall, the heavy metal load value of atmospheric deposition to the soil and water bodies, and the deduction reduction of heavy metals in the soil and heavy metal deposition by organisms. Then, combined with the emissions from point sources of heavy metal pollution, the predicted value of heavy metal pollution is calculated to comprehensively calculate the evolution process of heavy metal pollution between water, land, air and life.

[0151] The present invention fully considers the exchange characteristics of heavy metal pollution at the interface between water, land, air and organisms, and accurately simulates the evolution process of heavy metal pollution between water, land, air and organisms based on weather changes and hydrological calculations. This allows for comprehensive numerical simulation of the spatiotemporal distribution of heavy metal pollution loads in the basin, and therefore enables more comprehensive tracking and prediction of the development trend of heavy metal pollution loads in the basin.

[0152] A third specific embodiment of the numerical prediction method for the evolution of heavy metal pollution load in a watershed according to the present invention:

[0153] A numerical prediction method for the evolution of heavy metal pollution load in a watershed comprises the following steps:

[0154] Step 1: Collect the water, land, and air heavy metal pollution data within the basin to be predicted using a pre-built heavy metal pollution collection model;

[0155] Step 2: Using the pre-built heavy metal parameter analysis model, the water, land and air heavy metal pollution data are processed to obtain the heavy metal transformation property parameters;

[0156] Step 3: Using the pre-built three-dimensional evolution model of heavy metals, based on the parameters of heavy metal transformation properties, simulate the transformation process of heavy metal pollution between water, land, air and organisms to obtain multi-dimensional evolution data of heavy metals;

[0157] Step 4: Use the pre-built heavy metal coupling prediction model to couple the heavy metal multi-dimensional evolution data with weather data and hydrological calculation data to obtain the migration data of heavy metals between water, land, air and organisms, so as to simulate the overall evolution process of heavy metal pollution and obtain the predicted value of heavy metal pollution.

[0158] like Figure 2 As shown, the fourth specific embodiment of the numerical prediction method for the evolution of heavy metal pollution load in a watershed of the present invention is as follows:

[0159] A numerical prediction method for the evolution of heavy metal pollution load in a watershed comprises the following steps:

[0160] S1: Based on the digital elevation data of the watershed to be predicted, the watershed space is discretized into several sub-watersheds, and the water system is extracted to construct a hydrological model.

[0161] S2: The land use type, soil type, soil properties, and vegetation type of the watershed are added to the hydrological model, and the sub-watersheds are spatially discretized again to obtain a hydrological calculation model. The hydrological calculation model is then used to deduce the evolution of point source heavy metal pollution loads in the watershed.

[0162] S3: Use the heavy metal pollution collection model to collect point source emission data of heavy metal pollution in the rivers of the basin, and data on heavy metal pollution content in the air and soil.

[0163] S4: Through the heavy metal parameter analysis model, the point source emission data of heavy metal pollution are processed to obtain the heavy metal transformation property parameters and the migration parameters of heavy metals between water, land, air and biological environments, and a heavy metal three-dimensional evolution model is established to simulate the migration and transformation process of non-point source heavy metal pollution between the water phase, suspended phase and sediment phase; the heavy metal pollution content data in the air and soil are processed to obtain the migration parameters of heavy metals between water, land, air and biological environments, which are used to calculate the migration process of heavy metals between water, land, air and biological environments.

[0164] S5: Taking into account the input of weather data, through the heavy metal coupling prediction model, the evolution of point source heavy metal pollution load and water, land and air generated heavy metal pollution load are coupled to complete the numerical prediction of the evolution of heavy metal pollution load in the basin.

[0165] In this embodiment S1, based on the digital elevation data of the watershed to be predicted, the watershed space is discretized into several sub-watersheds, and the water system is extracted to construct a hydrological model as follows:

[0166] Using the basin terrain elevation in digital elevation data (DEM), the basin area threshold is set, which can be set from 0.1 to 100 square kilometers to determine the sub-basin range. At the same time, the location where the slope is greater than 10% in the digital elevation data is defined as the sub-basin boundary, and the river range is distinguished to determine the water system; then the basin outlet is selected, and the entire basin is divided into several sub-basins that conform to the basin's geographical characteristics and natural flow characteristics, recorded as The hydrological model is used for subsequent hydrological numerical calculations and can simulate runoff on the surface, in rivers, and in the soil of the basin.

[0167] In this embodiment S2, the land use type, soil type, soil properties, and vegetation type of the watershed are added to the hydrological model, and the sub-watersheds are spatially discretized again to obtain a hydrological calculation model, which serves as a carrier for calculating water balance and material transport. The hydrological calculation model includes the following steps:

[0168] S21: Collect land use classification data in the watershed to be predicted, and distinguish the types of cultivated land, forest land, pasture, industrial land, residential land, water area, pesticide and fertilizer use information, and other land use types in the watershed.

[0169] S22: Obtain the distribution of soil types and the physical and chemical properties of soil in the watershed. The properties of different soils mainly include the structure of the soil layer, the effective moisture available in the soil layer, the saturated hydraulic conductivity coefficient, the wet density of the soil, the soil erosion factor, and the types and contents of heavy metals in the soil.

[0170] S23: Obtain the vegetation types and distribution in the watershed, and distinguish plant communities with different surface coverage, such as forests, grasslands, shrubs, deserts, meadows, and swamps.

[0171] S24: Based on the above land use classification, soil properties and vegetation type distribution, the sub-basins divided in S1 are subdivided, that is, the sub-basins are divided into (1≤ ≤n, n is the total number of sub-basins) and superimpose the land use type distribution and soil type distribution contained in it to construct a hydrological calculation unit, and make each hydrological calculation unit Has a single land use type and soil type ,Right now Finally, the entire basin is spatially discretized into a hydrological calculation model, and a hydrological variable matrix is ​​established on each unit to store hydrological calculation variables to support the water volume between hydrological calculation units and rivers, and between hydrological calculation units. Hydrological variable matrix at each moment The expression is as follows:

[0172]

[0173] in, is the soil moisture content; is the rainfall; is the surface runoff; is the evaporation amount; is the infiltration amount; is the underground runoff.

[0174] S25: For each river defined in S1, construct a river calculation unit, and set the river runoff variable matrix in the river calculation unit to store the river evolution calculation variables for river evolution calculation and heavy metal load transmission calculation. River runoff variable matrix at time The expression is as follows:

[0175]

[0176] in, is the river runoff; is the amount of river water; is the mass concentration of heavy metals.

[0177] In this embodiment S3, the heavy metal pollution collection model is used to collect point source emission data of heavy metal pollution in the river basin and heavy metal pollution content data in the air and soil. The specific steps are as follows:

[0178] S31: Using the heavy metal pollution collection model, collect point source emission data on heavy metal pollution in the basin's rivers, construct a point source emission database, and consider the heavy metal load input from these point sources in subsequent numerical calculations. The point source emission database is constructed based on the daily load constant method and includes data on point source locations, daily runoff, daily sediment load, and daily heavy metal load.

[0179] S32: Using the heavy metal pollution collection model, collect data on heavy metal pollution levels in the air and soil of the watershed, construct an air and land pollution database, and factor the heavy metal load input from this area into subsequent numerical calculations. The air and land pollution database is constructed using the monthly average load constant method and includes data on the extent of the polluted area, the monthly average soil heavy metal load, and the monthly average atmospheric heavy metal load.

[0180] In this embodiment S4, the point source emission data of heavy metal pollution is processed using a heavy metal parameter analysis model to obtain heavy metal transformation property parameters, and a heavy metal three-dimensional evolution model is established to simulate the migration and transformation process of non-point source heavy metal pollution between the water phase, suspended phase, and sediment phase; the heavy metal pollution content data in the air and soil are processed to obtain the migration parameters of heavy metals between water, land, air, and living organisms, which are used to calculate the migration process of heavy metals between water, land, air, and living organisms. The specific steps are as follows:

[0181] S41: Collect the heavy metal transformation property parameters obtained through experiments or surveys, including the longitudinal diffusion coefficient , calculate the adsorption coefficient , the partition coefficient between sediment and water , desorption coefficient , the distribution coefficient of heavy metals in suspended matter and water , comprehensive sedimentation velocity , comprehensive constant of settlement influence , resuspension coefficient .

[0182] Longitudinal diffusion coefficient To reflect the migration and diffusion of substances in rivers, the empirical formula Fischer can be used for calculation. The specific calculation formula is as follows:

[0183]

[0184] Where, is the average depth of the river, is the average width of the river, is the average flow velocity of the river, is the acceleration due to gravity, is the hydraulic gradient, which can generally be between 1 and .

[0185] Partition coefficient of heavy metals in suspended matter and water It is the ratio of the concentration of suspended heavy metals to the concentration of dissolved heavy metals at equilibrium, and its expression is as follows:

[0186]

[0187] in, is the heavy metal content in the particles, The coefficient is obtained by sampling and measuring the heavy metal content in water and soil samples, and the general value range is 10 3 to 10 6 between.

[0188] Partition coefficient between sediment and water It is the ratio of the concentration of heavy metals in the sediment to that in the dissolved state under the three-phase equilibrium state, and its expression is as follows:

[0189]

[0190] in, is the heavy metal content in the sediment, The coefficient is obtained by sampling and measuring the heavy metal content in sediment and soil samples, and the general value range is 10 3 to 10 6 between.

[0191] The comprehensive coefficient, resuspension coefficient and desorption coefficient can be determined by the inverse test algorithm. The general value range is to between.

[0192] Considering that heavy metal pollutants are discharged into water bodies, they undergo adsorption and desorption with suspended sediment particles in the water body. A portion of the heavy metals will be adsorbed onto the surface of the suspended sediment particles and move with the suspended sediment, undergoing convection and diffusion migration with the heavy metals in the water body. At the same time, the migration and transformation of another portion of heavy metals due to the sedimentation of suspended sediment and the resuspension of bed sediment are considered. Based on the heavy metal transformation property parameters and convection and diffusion characteristics, a heavy metal three-dimensional evolution model is established to characterize the mass concentrations of dissolved and suspended heavy metals. The calculation formula is as follows:

[0193]

[0194]

[0195] in, is the source term of dissolved and suspended heavy metals, which can be regarded as the exchange rate of heavy metal antimony between sediment and water body in unit water depth. is the mass concentration of heavy metals; is the time step; is the longitudinal component of the water cross-section velocity; is the average flow velocity of the cross section; is the longitudinal position component; is the mass concentration of dissolved heavy metals; is the mass concentration of suspended heavy metals; For water depth.

[0196] S42: Set the initial heavy metal concentration at the beginning of the watershed and the boundary conditions of heavy metal concentration at the boundary of the watershed model, that is, the time series of heavy metal concentration. Then, use the implicit difference method to discretize the above equations to obtain the implicit difference equation group, which is expressed as follows:

[0197]

[0198]

[0199]

[0200]

[0201] in, For the watershed node At the moment The heavy metal concentration, For the watershed node At the moment The heavy metal concentration, For the watershed node At the moment The heavy metal concentration, For the watershed node At the moment The heavy metal concentration, For the watershed node At the moment The heavy metal concentration, is the grid size, is the time step, is the time step, is the vertical position component.

[0202] Then, based on the implicit difference equations, the three-dimensional evolution model of heavy metals is transformed to obtain a new set of calculation equations, as follows:

[0203]

[0204]

[0205]

[0206]

[0207] in, is the undetermined coefficient.

[0208] The equations are written as a tridiagonal matrix and solved using the pursuit method to obtain the heavy metal mass concentration at each node at each moment. The specific expression is as follows:

[0209]

[0210]

[0211]

[0212]

[0213] in, is the unknown coefficient, For the watershed node 0 at time heavy metal concentrations.

[0214] S43: Through soil sampling and experiments, the data on heavy metal leaching in the soil are processed based on the types of heavy metals, soil types, soil heavy metal content, and the use of pesticides and fertilizers. The leaching amount of heavy metals in the soil under different rainwater pH and rainfall duration is fitted using the heavy metal rainfall leaching law prediction equation to obtain the equation parameters for predicting the rainfall leaching law of heavy metals in the soil, and the soil heavy metal leaching law due to rainfall is obtained.

[0215] The heavy metal rainfall leaching equation can be fitted using forms such as the first-order kinetic equation, the double-constant rate equation, the parabolic equation, and the modified kinetic equation Elovich.

[0216] The first-order kinetic equation is as follows:

[0217]

[0218] The double-constant rate equation has the following form:

[0219]

[0220] The equation of a parabola is as follows:

[0221]

[0222] The modified Elovich form of the kinetic equation is as follows:

[0223]

[0224] in, is the amount of heavy metal leaching, is the equivalent rainfall duration, is the fitting constant, typically ranging from -100 to 100.

[0225] For the selected heavy metal rainfall leaching law prediction equation form, given a set of rainfall duration and corresponding soil heavy metal leaching data under different rainwater pH, a set of equation parameters under different rainwater pH are obtained through equation fitting analysis. , which is subsequently used to predict the amount of heavy metal leaching from soil under given rainfall pH and duration conditions.

[0226] S44: Through sampling experiments or surveys of the atmosphere, soil, and water, the atmospheric deposition flux of heavy metals is calculated based on the type and content of heavy metals, soil type, and dry and wet conditions. The expression is as follows:

[0227]

[0228]

[0229] in, is the wet deposition flux, is the dry deposition flux, is the heavy metal content of wet deposition, is the heavy metal content of dry deposition, is the wet deposition rate, is the dry deposition rate, is the air pressure factor, The above data were obtained through experiments and surveys. Under given rainfall conditions, the air pressure, average wind speed, and watershed area were combined to obtain the deposition load of heavy metals from the atmosphere into soil and water.

[0230] S45: Based on the types and concentrations of heavy metals and vegetation cover in the watershed, determine the biological absorption ratio of soil heavy metals and the biological filtration reduction ratio of atmospheric heavy metal deposition through experiments or surveys, with values ​​ranging from 0 to 1. These values ​​will be deducted from the soil heavy metal load and atmospheric heavy metal deposition load in the corresponding area during subsequent calculations.

[0231] In this embodiment S5, considering the input of weather data, the heavy metal coupled prediction model is used to couple the evolution of point source heavy metal pollution load and the evolution of water, land, and air-borne heavy metal pollution load to complete the numerical prediction of the evolution of heavy metal pollution load in the basin. The specific steps are:

[0232] S51: Collect meteorological data from weather stations within the basin, including annual maximum wind speed, daily maximum rainfall, monthly rainfall, air pressure and rainwater pH observations, and calculate soil moisture and precipitation for hydrological simulation.

[0233] S52: Based on meteorological data, the initial hydrological conditions and meteorological data conditions of the basin are set, including soil moisture, rainfall, runoff, evaporation, infiltration, and underground runoff; then, a hydrological simulation is performed on the discrete hydrological calculation model of the basin, and based on the water balance principle, the runoff changes in the surface, rivers, soil, and groundwater of the basin are calculated, and the water balance between hydrological calculation units is calculated. Hydrological runoff calculations can be calculated using the surface runoff curve method (SCS) or the infiltration method (Green & Ampt). The water balance calculation equation is:

[0234]

[0235] in, for Soil moisture content at the moment; is the initial soil moisture content; is the rainfall; is the surface runoff; is the evaporation amount; is the infiltration amount; is the underground runoff.

[0236] The flow velocity of the river is further calculated using the Manning formula , and calculate the cross-sectional area of ​​the flow based on the runoff belonging to the river channel , and calculate the river depth at the same time , the corresponding calculation formula is as follows:

[0237]

[0238]

[0239]

[0240]

[0241]

[0242] in, is the flow velocity of the river; is the hydraulic radius of the section; is the river slope; is the roughness; is the cross-sectional area of ​​the flow; is the amount of river water; is the river runoff, which is obtained by the influx of surface runoff; is the calculation time step; is the length of the river section; is the width of the riverbed; It is the reverse slope of the river channel; For water depth.

[0243] S53: Based on S3, point source heavy metal pollution load is considered, and S4, heavy metal load in soil leached by rainfall, heavy metal load deposited by the atmosphere into soil and water, and biological deduction and reduction of heavy metals in soil and heavy metal deposition, and the mass concentration of dissolved heavy metals is combined by superimposing solutes. and the mass concentration of suspended heavy metals The source term is used to obtain the predicted value of heavy metal pollution, so that the mass concentration of point source and non-point source heavy metals as well as land- and air-borne heavy metal pollution loads are simultaneously considered in the calculation process. The flow velocity and water depth of the river channel are obtained through the water volume calculation described in S52. The flow velocity and water depth are then transferred to the heavy metal three-dimensional evolution model to calculate the distribution, migration and component transformation process of the heavy metal pollution load in the watershed, and finally the heavy metal mass concentration at each moment in the river channel within the watershed is obtained.

[0244] A specific embodiment of applying the present invention to predict the evolution of heavy metal cadmium pollution load in a certain river basin:

[0245] The method for predicting the evolution of heavy metal cadmium pollution load in a certain river basin using the present invention is as follows:

[0246] S1: Based on the digital elevation data of a watershed, the watershed space is discretized into several sub-watersheds, the water system is extracted, and a hydrological model is constructed, which specifically includes the following:

[0247] The GIS technology is used to analyze the basin terrain elevation in the digital elevation data (DEM). Based on the scope of the basin to be predicted, the basin area threshold is set to 90ha. The pixels of the DEM are traversed to obtain the location information of the DEM with a slope greater than 10%. Then, based on the location information, the sub-basin boundaries are distinguished, and the rivers and water systems are defined. The entire basin is divided into sub-basins that conform to the basin's geographical characteristics and natural runoff characteristics. Specifically, they are recorded as There are nine sub-basins, each with a river, for a total of nine rivers in the basin. The sub-basin division will be used in subsequent hydrological numerical calculations.

[0248] S2: Collect the land use type, soil type, soil properties and vegetation type of the watershed and spatially discretize the above sub-watersheds again to obtain a hydrological calculation model, which serves as the carrier for the model to calculate water balance and material transport. The specific steps are as follows:

[0249] S21: By collecting remote sensing data, we can obtain the land use classification data in the watershed to be predicted, and subdivide the watershed to be predicted into three land use types: cultivated land, forest land, and industrial land.

[0250] S22: By collecting remote sensing data and searching literature, the distribution and physical and chemical properties of two soil types in the basin were obtained, namely highly active leaching soil and saturated vertisol. The properties of different soils mainly include the structure of the soil layer, the effective moisture available in the soil layer, the saturated hydraulic conductivity coefficient, the wet density of the soil, the soil erosion factor and the content of heavy metal cadmium in the soil.

[0251] S23: By collecting remote sensing data and searching literature, we can obtain the vegetation types and distribution in the watershed and distinguish the three plant communities covering the ground: forest, grassland, and shrubland.

[0252] S24: Based on the above land use classification, soil properties and vegetation types The location distribution and combination in the 9 sub-basins are further split into several hydrological calculation units, and each hydrological calculation unit has a single land use type and soil type. Finally, the entire basin is discretized into 49 hydrological calculation units from space, and a hydrological variable matrix is ​​established on each unit to store hydrological calculation variables, which are used to support the water volume between hydrological calculation units and rivers, and between hydrological calculation units.

[0253] Then, the i-th hydrological calculation unit is Hydrological variable matrix at each moment The expression is as follows:

[0254]

[0255] in, is the soil moisture content; is the rainfall; is the surface runoff; is the evaporation amount; is the infiltration amount; is the underground runoff.

[0256] S24: For each river section defined in S1, a river calculation unit is established, and a river runoff variable matrix is ​​set to store river evolution calculation variables, which are used for river evolution calculation and heavy metal load transmission calculation.

[0257] The calculation unit of the jth river (j=1,2,…,9) is River runoff variable matrix at time The expression is as follows:

[0258]

[0259] in, is the river runoff; is the amount of river water; is the mass concentration of heavy metal cadmium.

[0260] S3: Use the heavy metal pollution collection model to collect point source emission data of heavy metal pollution in the river basin, and data on heavy metal pollution content in the air and soil. The specific steps are as follows:

[0261] S31: Using the heavy metal pollution collection model, collect the point source emission data of heavy metal pollution in the river basin, build a point source emission database, and consider the heavy metal load input of this part of the point source in the subsequent numerical calculation. The point source emission database is constructed based on the daily load constant method. The location of the heavy metal point source is distributed in and The river confluence points are recorded, and the daily runoff time series, daily sediment load time series and daily heavy metal cadmium load time series of the corresponding source items are recorded, which are then superimposed into the heavy metal three-dimensional evolution model as heavy metal cadmium mass concentration source items.

[0262] S32: Using the heavy metal pollution collection model, collect data on heavy metal pollution levels in the air and soil of the watershed, construct an air and land pollution database, and factor the heavy metal load input from this area into subsequent numerical calculations. The air and land pollution database is constructed using the monthly average load constant method and includes the monthly average soil heavy metal load and the monthly average atmospheric heavy metal load within the sub-watershed.

[0263] S4: Using the heavy metal parameter analysis model, collect the transformation property parameters of heavy metal cadmium and establish a three-dimensional evolution model of heavy metals; process the heavy metal pollution content data in the air and soil to obtain the migration parameters of heavy metals between water, land, air and organisms, which are used to calculate the migration process of heavy metals between water, land, air and organisms. The specific steps are as follows:

[0264] S41: Collect heavy metal transformation parameters through experiments or surveys, including the calculation of the longitudinal diffusion coefficient of heavy metals using the empirical formula Fischer , calculate the adsorption coefficient , the partition coefficient between sediment and water , desorption coefficient , the distribution coefficient of heavy metals in suspended matter and water , comprehensive sedimentation velocity , comprehensive constant of settlement influence , resuspension coefficient .

[0265] Based on the parameters of heavy metal transformation properties, a three-dimensional evolution model of heavy metals was established, and its expression is as follows:

[0266]

[0267]

[0268] in, is the mass concentration of heavy metals; For time; is the longitudinal component of the water cross-section velocity; is the average flow velocity of the cross section; is the longitudinal position component; is the mass concentration of dissolved heavy metals; is the mass concentration of suspended antimony; For water depth.

[0269] S42: Set the initial concentration of heavy metals at the beginning of the watershed to 0, set the heavy metal concentration at the boundary of the watershed model to be constant to 0, use the implicit difference method to discretize the above equation, and then use the triangular matrix pursuit method to solve it.

[0270] S43: Through soil sampling and experiments or literature research, the leaching amount data of soil heavy metals under different rainwater pH and multiple rainfall durations are fitted using the modified kinetic equation Elovich form. The modified kinetic equation Elovich form is as follows:

[0271]

[0272] in, is the leaching amount of heavy metal cadmium, is the equivalent rainfall duration, and is the fitting constant.

[0273] When the pH value of rainwater is 5, we get and The values ​​are 45 and 6; when the pH value of rainwater is 6, we get and The values ​​are 38 and 5.4; when the pH value of rainwater is 7, we get and The values ​​are 35 and 5.1; when the pH value of rainwater is 5, we get and The values ​​are 31 and 5.0. and The values ​​are fitted using exponential functions to obtain and The calculation formula of the fitting function of pH value is as follows:

[0274]

[0275]

[0276] in, 、 、 and is the fitting constant of the above parameters, and pH is the acidity and alkalinity of rainwater.

[0277] will be about and The fitting function of The solution equation is thus formed Regarding the calculation formula for rainfall duration and rainwater pH, the amount of heavy metal cadmium leached in the soil was obtained based on rainfall and rainwater pH in the subsequent simulation.

[0278] S44: Through sampling experiments or surveys of the atmosphere, soil, and water, calculate the atmospheric deposition flux of heavy metals based on the types and contents of heavy metals, soil types, and dry and wet conditions:

[0279]

[0280]

[0281] in, is the wet deposition flux, is the dry deposition flux, is the heavy metal content of wet deposition, is the heavy metal content of dry deposition, is the wet deposition rate, is the dry deposition rate, is the pressure factor, which is obtained by the ratio of actual pressure to reference pressure. is the wind speed factor, which is obtained by the ratio of the reference average wind speed to the actual average wind speed.

[0282] Furthermore, the wet deposition flux and dry deposition flux of heavy metal cadmium are 0.9 and 0.7 , under given rainfall conditions, the deposition load value of heavy metals from the atmosphere to the soil and water bodies is obtained by combining the actual air pressure, actual average wind speed and basin area.

[0283] S45: Based on the types and concentrations of heavy metals and vegetation cover in the watershed, determine the biological absorption ratio of soil heavy metals and the biological filtration reduction ratio of atmospheric heavy metal deposition through experiments or surveys, with values ​​ranging from 0 to 1. These values ​​will be deducted from the soil heavy metal load and atmospheric heavy metal deposition load in the corresponding area during subsequent calculations.

[0284] S5: Using the heavy metal coupled prediction model, collect weather data from the past 10 years and couple the evolution of point source and land-based and air-based heavy metal pollution loads. The specific steps are as follows:

[0285] S51: Collect meteorological data from the meteorological stations in the basin. There is one meteorological station in the basin. The data include the annual maximum wind speed, daily maximum rainfall, monthly rainfall, and rainwater pH observations over the past 10 years. Then, based on the meteorological data, calculate soil moisture and precipitation, and statistically form the meteorological change patterns of the basin and apply them to hydrological simulations.

[0286] S52: Set the initial hydrological conditions for the basin, and based on the above meteorological data conditions, calculate soil moisture and precipitation. Perform hydrological simulation on the basin's discrete hydrological calculation model. Based on the water balance principle, calculate the changes in runoff volume on the basin's surface, rivers, soil, and groundwater. Also calculate water transfer and sediment erosion between hydrological calculation units. The calculation formula for hydrological runoff is as follows:

[0287]

[0288]

[0289] in, is the surface runoff; is the rainfall; is the initial loss; S is the infiltration amount; CN is a constant, which is related to the initial soil moisture, soil type, vegetation cover type, hydrological conditions and slope.

[0290] The water balance equation is used to calculate the water transfer of the hydrological calculation unit. The calculation formula is as follows:

[0291]

[0292] in, for Soil moisture content at the moment; is the initial soil moisture content; is the rainfall; is the surface runoff; is the evaporation amount; is the infiltration amount; is the underground runoff.

[0293] Calculate the flow velocity of a river using the Manning formula , and calculate the flow cross-sectional area based on the runoff and river depth , and its corresponding calculation formula is as follows:

[0294]

[0295]

[0296]

[0297]

[0298]

[0299] in, the flow rate of the river; is the hydraulic radius of the section; is the river slope, with a value of 0.001; is the roughness, which is 0.03; is the cross-sectional area of ​​the flow; is the amount of river water; is the river runoff, which is obtained by the influx of surface runoff; For the calculation time step, 1 day is selected; is the length of the river section; is the width of the riverbed; It is the reverse slope of the river channel; For water depth.

[0300] S53: Consider the pollution load of point source heavy metal cadmium, and superimpose the amount of heavy metal cadmium leached from the soil due to rainfall, the heavy metal cadmium load deposited into the soil and water by the atmosphere, the deduction of heavy metal cadmium in the soil and heavy metal cadmium deposition by organisms, the mass concentration of dissolved heavy metal cadmium, and the mass concentration of suspended heavy metal cadmium; then calculate the flow rate and water depth of the river channel through the watershed water volume; then solve the heavy metal three-dimensional evolution model based on the flow rate and water depth to simulate the distribution, migration and component transformation process of the heavy metal cadmium pollution load in the basin, and finally obtain the mass concentration of heavy metal cadmium in the river channel at each moment in the basin, which can be seen in [1]. Figure 3 . Figure 3 The figure shows the predicted concentration values ​​of heavy metal concentrations in key downstream sections as the calculation period changes after heavy metal pollutants are discharged from upstream, as shown by the solid black dots in the figure. The unit of the predicted concentration value is micrograms per liter. , the unit of time calculation period is hour The present invention can accurately simulate the changing trends of heavy metal pollution loads in a watershed, facilitating the prevention and management of heavy metal pollution in watershed waters. This method comprehensively considers point and non-point sources, as well as land and air-borne heavy metal pollution loads, enabling a more comprehensive numerical simulation of the spatiotemporal distribution of heavy metal pollution loads in a watershed, and enabling more comprehensive tracking and prediction of changes in heavy metal pollution loads within the watershed.

[0301] An embodiment of a device applying the method of the present invention:

[0302] An electronic device comprising:

[0303] one or more processors;

[0304] a storage device for storing one or more programs;

[0305] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned numerical prediction method for the evolution of heavy metal pollution load in a watershed.

[0306] A computer medium embodiment of the method of the present invention:

[0307] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned numerical prediction method for the evolution of heavy metal pollution load in a watershed.

[0308] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, optical storage, etc.) containing computer-usable program code.

[0309] The present application is described in terms of flowcharts or / and block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process or / and block in the flowchart or / and block diagram, as well as the combination of processes or / and blocks in the flowchart or / and block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0310] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0311] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0312] The model in this application is an object that objectively describes the morphological structure with the help of physical or virtual representation. The object is not equal to the physical body and is not limited to physical and virtual. It can be a data processing function, software program, processing mode, usage method, operation method, workflow, application process, electronic hardware, circuit module, processing system, system imitation or simulation object.

[0313] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field can still modify or replace the specific implementation methods of the present invention. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be included in the scope of protection of the claims of the present invention.

Claims

1. A numerical prediction method for the evolution of heavy metal pollution load in a watershed, characterized by: Includes the following: Through the pre-built heavy metal pollution collection model, collect the water, land and air heavy metal pollution data in the basin to be predicted; Using the pre-built heavy metal parameter analysis model, the water, land and air heavy metal pollution data are processed to obtain the heavy metal transformation property parameters; Using a pre-built three-dimensional heavy metal evolution model and based on heavy metal transformation parameters, we simulated the leaching of heavy metals from soil due to rainfall, the atmospheric deposition of heavy metals, and the changes in heavy metal loads in water bodies. This generated multi-dimensional heavy metal evolution data, which was used to characterize the migration and changes of heavy metals between land, water, and air. The method for simulating the leaching of heavy metals from soil due to rainfall is as follows: Based on the parameters of heavy metal transformation properties, obtain the soil heavy metal content and the use of pesticides and fertilizers; Based on the soil heavy metal content, pesticide and fertilizer usage information, equivalent rainfall duration, and multiple unknown variable parameters, a heavy metal rainfall leaching equation was constructed. The heavy metal rainfall leaching equation was used to fit the soil heavy metal leaching data under different rainwater pH and multiple rainfall durations, and the fitting results were obtained. According to the fitting results, the values ​​of variable parameters under different rainwater pH values ​​are determined; Summarize the variable parameter values ​​of different rainwater pH values, and then use the exponential function to fit them to obtain the fitting function of the variable with respect to pH value; Substitute the fitting function of the variable related to pH into the heavy metal rainfall leaching equation to form a calculation formula for the heavy metal leaching amount related to rainfall duration and rainwater pH, thereby simulating the leaching process of heavy metals from the soil due to rainfall; The method for simulating the atmospheric heavy metal deposition process is as follows: Determine the type of heavy metals, soil type, and dry and wet conditions based on the parameters of heavy metal transformation properties; Determine heavy metal deposition information based on heavy metal types, soil types, and dry and wet conditions; Heavy metal deposition information includes wet deposition heavy metal content, dry deposition heavy metal content, wet deposition rate, and dry deposition rate; Based on rainfall conditions and air pressure information, obtain actual air pressure and reference air pressure; The ratio of the actual air pressure to the reference air pressure is used as the air pressure factor; Based on rainfall conditions and average wind speed information, obtain reference average wind speed and actual average wind speed; The ratio of the reference average wind speed to the actual average wind speed is used as the wind speed factor; Based on the heavy metal deposition information, air pressure factors, and wind speed factors, the calculation formulas for the wet and dry deposition fluxes of heavy metals were constructed. The wet and dry deposition flux calculation formulas of heavy metals are jointly solved to obtain the load of heavy metals deposited from the atmosphere to the soil and water bodies, thus simulating the atmospheric heavy metal deposition process. Using a pre-built heavy metal coupling prediction model, the multi-dimensional evolution data of heavy metals are coupled with weather data and hydrological calculation data to calculate the evolution process of heavy metal pollution between water, land and air, and obtain the predicted value of heavy metal pollution.

2. The numerical prediction method for the evolution of heavy metal pollution load in a watershed according to claim 1, characterized in that: The method for collecting water, land, and air heavy metal pollution data within the basin to be predicted using the pre-built heavy metal pollution collection model is as follows: Obtain the location information of the watershed to be predicted; Based on the location information of the watershed to be predicted, collect point source emission data of heavy metal pollution in the watershed to be predicted; Point source emission data shall at least include the location of the point source, watershed runoff, watershed sediment load, and heavy metal load; According to the point source emission data, a point source emission database is constructed based on the daily load constant method; Based on the location information of the watershed to be predicted, collect data on heavy metal pollution content in the air and soil of the watershed; Heavy metal pollution data include the monthly average soil heavy metal load and the monthly average atmospheric heavy metal load in the basin; Based on the heavy metal pollution content data and the monthly average load constant method, an air and land pollution database was constructed; The point source emission database and the air and land pollution database are aggregated to form the water, land and air heavy metal pollution data, which are used as the heavy metal load input for numerical calculations.

3. The numerical prediction method for the evolution of heavy metal pollution load in a watershed according to claim 1, characterized in that: The method for processing the water, land, and air heavy metal pollution data using the pre-built heavy metal parameter analysis model to obtain the heavy metal transformation property parameters is as follows: Based on the heavy metal pollution data on land, water and air, obtain the types of heavy metals, soil types, longitudinal diffusion coefficients of heavy metals, calculated adsorption coefficients, and distribution coefficients between sediment and water, as well as dry and wet conditions; Determine the desorption coefficient of heavy metals and the distribution coefficient of heavy metals between suspended matter and water based on the type of heavy metals, the longitudinal diffusion coefficient of heavy metals, the measured adsorption coefficient and the distribution coefficient between sediment and water; The comprehensive sedimentation velocity, comprehensive sedimentation effect constant and resuspension coefficient of heavy metals are calculated using the desorption coefficient of heavy metals and the distribution coefficient of heavy metals in suspended matter and water. Determine soil heavy metal content and pesticide and fertilizer usage information based on the type of heavy metals, soil type, and pesticide and fertilizer usage regulations; The types of heavy metals, soil types, longitudinal diffusion coefficients of heavy metals, measured adsorption coefficients and distribution coefficients between sediment and water and dry and wet conditions, desorption coefficients of heavy metals, distribution coefficients of heavy metals in suspended matter and water bodies, comprehensive sedimentation velocity of heavy metals, comprehensive constants affecting sedimentation, resuspension coefficients, equation parameters, soil heavy metal content, and information on the use of pesticides and fertilizers were summarized to obtain the parameters of heavy metal transformation properties.

4. The numerical prediction method for the evolution of heavy metal pollution load in a watershed according to claim 1, characterized in that: It also includes using a pre-built three-dimensional evolution model of heavy metals to simulate the biological reduction process of heavy metals based on the parameters of heavy metal transformation properties. The method is as follows: Determine the vegetation cover type based on the soil type and the geographical location of the watershed to be predicted; According to the vegetation cover type and heavy metal transformation parameters, the absorption ratio of soil heavy metals by organisms and the filtration reduction ratio of atmospheric heavy metal deposition by organisms were obtained. According to the absorption ratio and filtration reduction ratio, the biological reduction amount of heavy metals is determined to achieve the simulation of the heavy metal reduction process.

5. The numerical prediction method for the evolution of heavy metal pollution load in a watershed according to claim 1, characterized in that: The method for obtaining the predicted value of heavy metal pollution is as follows: Substitute the rainfall data of the basin to be predicted into the calculation formula of heavy metal leaching amount related to rainfall duration and rainwater pH to obtain the heavy metal leaching amount of the basin to be predicted; According to the atmospheric heavy metal deposition process, the calculation formulas for the wet deposition flux and the dry deposition flux of heavy metals are determined; Based on the meteorological information and area of ​​the basin to be predicted, and combined with the calculation formulas for wet deposition flux and dry deposition flux of heavy metals, the deposition load value of heavy metals from the atmosphere to the soil and water bodies is calculated; Use point source emission data of heavy metals as new land, water and air heavy metal pollution data; Substitute the new land, water, and air heavy metal pollution data and hydrological calculation data into the process of heavy metal load changes in water bodies, and by superimposing solutes, merge the mass concentration source terms of dissolved heavy metals and the mass concentration source terms of suspended heavy metals into the transformation prediction calculation equations to construct the overall prediction calculation equations. The overall prediction calculation equations are solved to obtain the heavy metal mass concentration at each moment in the basin, that is, the predicted value of heavy metal pollution.

6. The numerical prediction method for the evolution of heavy metal pollution load in a watershed according to claim 5, characterized in that: The method of constructing the hydrological calculation model is as follows: Collect land use classification data of the watershed to be predicted; Obtain soil type distribution information and soil attribute data based on land use classification data; Obtain several sub-basins of the basin to be predicted, and subdivide the sub-basins according to soil type distribution information and soil attribute data, and superimpose the soil type distribution information and soil attribute data to obtain several hydrological calculation units; Each hydrological calculation unit has a single land use type and soil type, and a hydrological variable matrix is ​​established on each hydrological calculation unit; According to the water area information, several river calculation units are constructed, and a river runoff variable matrix is ​​set on each river calculation unit for river evolution calculation and heavy metal load transmission calculation; Several hydrological calculation units and river calculation units are coupled to obtain a hydrological calculation model, which serves as a carrier for calculating water balance and material transport.

7. The numerical prediction method for the evolution of heavy metal pollution load in a watershed according to claim 6, characterized in that: The method to obtain several sub-basins of the basin to be predicted is as follows: Obtain the location information of the watershed to be predicted; Based on the location information of the watershed to be predicted, digital elevation data of the watershed to be predicted is obtained; Based on the digital elevation data of the watershed to be predicted, the boundary location information with a slope greater than 10% is obtained; Determine the boundaries of several sub-basins through boundary location information; Determine the sub-basin range based on the sub-basin boundary and basin area threshold; According to the scope of each sub-basin, the outlet of each sub-basin is determined, so that the entire basin is divided into several sub-basins that conform to the basin's geographical characteristics and natural runoff characteristics.

8. A numerical prediction system for the evolution of heavy metal pollution load in a watershed, characterized by: It includes: one or more processors; a storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement a numerical prediction method for the evolution of heavy metal pollution load in a watershed as described in any one of claims 1-7.

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