Urban water black and odor returning risk assessment system and method based on multi-interface coupling

Abstract

The invention provides an urban water black and odor returning risk assessment system and method based on multi-interface coupling, and relates to the technical field of water environment monitoring and assessment. A parameter acquisition module is used for acquiring environment monitoring data acquired by a sensor; the core function module is used for simulating the exchange flux of black and odorous substances in a land-water interface, a gas-water interface and a mud-water interface and substance accumulation information in land pipelines, water bodies and sediments based on environment monitoring data through a system dynamics model, and determining a pollutant simulation result; the model verification module is used for evaluating the model performance based on the calibration set and the verification set after parameter calibration through the model evaluation unit; and the scene analysis module is used for performing full-coupling simulation on water black and odor returning risks corresponding to various preset city scenes according to the pollutant simulation result when the model performance evaluation is passed, and determining a target risk evaluation result. According to the method, the accuracy of evaluating the black and odor returning risk of the urban water body can be remarkably improved.

Description

Technical Field

[0001] This invention relates to the technical field of water environment monitoring and assessment, and in particular to a risk assessment system and method for urban water bodies to turn black and smelly again based on multi-interface coupling. Background Technology

[0002] In the field of urban water environment management, the problem of black and odorous water bodies has always been an environmental challenge that urgently needs to be addressed. Currently, research on the migration and transformation processes of black and odorous substances in urban water bodies mainly focuses on the simulation and prediction of single interfaces. However, this approach is difficult to comprehensively describe the migration and transformation patterns of substances causing black and odorous conditions. At the same time, existing models often employ complex hydrodynamic equations, resulting in a large computational burden, which is not conducive to rapid prediction and management decisions. Furthermore, existing schemes lack a systematic consideration of the exchange of substances between multiple media such as land, water, atmosphere, and sediments, and generally suffer from the problem of fragmented interface processes. They fail to fully consider the interaction relationships between land pipelines, land-water interfaces, air-water interfaces, and mud-water interfaces, resulting in an inability to comprehensively reflect the migration and transformation processes of substances between multiple interfaces, leading to one-sided assessment results. In addition, most existing models adopt steady-state or quasi-steady-state assumptions, making it difficult to simulate the dynamic impact of external factors such as rainfall on black and odorous water bodies. Especially when simulating water quality changes under sudden pollution events or extreme weather conditions, the accuracy of the prediction results is low, thus affecting the accuracy of the assessment of the risk of urban water bodies turning black and odorous again. Summary of the Invention

[0003] In view of this, the purpose of this invention is to provide a system and method for assessing the risk of urban water bodies turning black and smelly again based on multi-interface coupling, which can significantly improve the accuracy of assessing the risk of urban water bodies turning black and smelly again.

[0004] In a first aspect, embodiments of the present invention provide a risk assessment system for the recurrence of black and odorous urban water bodies based on multi-interface coupling. The system includes: a parameter acquisition module, a core function module, a model verification module, and a scenario analysis module. The parameter acquisition module acquires environmental monitoring data collected by sensors, including constant parameters and dynamic environmental factors. The core function module simulates the exchange flux of black and odorous substances in land-based pipelines, land-water interfaces, air-water interfaces, and mud-water interfaces, as well as the accumulation information of substances in land-based pipelines, water bodies, and sediments, based on the environmental monitoring data using a system dynamics model, and determines the pollutant simulation results. The model verification module divides the environmental monitoring data into a calibration set and a validation set, and evaluates the model performance based on the calibrated calibration and validation sets using a model evaluation unit. The scenario analysis module, when the model performance evaluation is passed, performs a fully coupled simulation of the risk of black and odorous water bodies corresponding to various preset urban scenarios based on the pollutant simulation results, and determines the target risk assessment results.

[0005] In one implementation, the core functional module includes: a land pipeline module; wherein, the land pipeline module is used to analyze and process the organic matter accumulation information, sulfide accumulation information and ammonium nitrogen accumulation information in the land pipeline according to the analysis model of material accumulation in the land pipeline, so as to determine the dynamic change information of black and odorous substances in the land pipeline.

[0006] In one embodiment, the core functional module includes: a land-water interface module; wherein, the land-water interface module is used to analyze and process the organic matter exchange information, sulfide exchange information and ammonium nitrogen exchange information at the land-water interface based on the pollutant concentration difference between the land and water bodies, and to determine the exchange flux of dissolved pollutants at the land-water interface.

[0007] In one embodiment, the core functional module includes: a gas-water interface module; wherein, the gas-water interface module is used to analyze and process the sulfide exchange information and ammonium nitrogen exchange information at the gas-water interface based on the pollutant concentration difference between the gas and the water body and in combination with the Henry's constant to balance the volatile state, and to determine the exchange flux of pollutants at the gas-water interface.

[0008] In one embodiment, the core functional module includes a mud-water interface module; wherein, the mud-water interface module is used to analyze and process the organic matter exchange information, sulfide exchange information and ammonium nitrogen exchange information at the air-water interface based on the pollutant concentration difference between sediment pore water and water body and a preset distribution coefficient, so as to determine the exchange flux of dissolved pollutants at the mud-water interface.

[0009] In one embodiment, the core functional module includes: a water body material accumulation module; wherein, the water body material accumulation module is used to analyze and process the organic matter accumulation information, sulfide accumulation information and ammonium nitrogen accumulation information in the water body according to the water body material accumulation analysis model, and determine the dynamic change information of black and odorous substances in the water body.

[0010] In one embodiment, the core functional module includes: a sediment accumulation module; wherein, the sediment accumulation module is used to analyze and process the organic matter accumulation information, sulfide accumulation information and ammonium nitrogen accumulation information in the sediment according to the sediment accumulation analysis model, and determine the dynamic change information of black and odorous substances in the sediment.

[0011] Secondly, embodiments of the present invention also provide a method for assessing the risk of urban water bodies turning black and smelly again based on multi-interface coupling. The method is applied to an urban water body blackening and smelling-again risk assessment system based on multi-interface coupling. The method includes: acquiring environmental monitoring data, wherein the environmental monitoring data includes constant parameters and dynamic environmental factors; analyzing and processing the constant parameters and dynamic environmental factors using land pipeline modules, land-water interface modules, air-water interface modules, mud-water interface modules, water body material accumulation modules, and sediment material accumulation modules, respectively, to determine pollutant simulation results, wherein the pollutant simulation results include: dynamic change information of black and smelly substances in land pipelines, exchange flux of dissolved pollutants at the land-water interface, exchange flux of pollutants at the air-water interface, exchange flux of dissolved pollutants at the mud-water interface, dynamic change information of black and smelly substances in water bodies, and dynamic change information of black and smelly substances in sediments; and, based on the pollutant simulation results, performing a fully coupled simulation of the risk of water bodies turning black and smelly again corresponding to various preset urban scenarios to determine the target risk assessment results.

[0012] Thirdly, embodiments of the present invention also provide a server, including a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement any of the methods provided in the first aspect.

[0013] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement any of the methods provided in the first aspect.

[0014] The embodiments of the present invention bring the following beneficial effects: This invention provides a system and method for assessing the risk of urban water bodies turning black and odorous again based on multi-interface coupling. The system includes: a parameter acquisition module, a core function module, a model verification module, and a scenario analysis module. The parameter acquisition module acquires environmental monitoring data collected by sensors, including constant parameters and dynamic environmental factors. The core function module uses a system dynamics model, based on the environmental monitoring data, to simulate the exchange flux of black and odorous substances in land-based pipelines, land-water interfaces, air-water interfaces, and mud-water interfaces, as well as the accumulation information of substances in land-based pipelines, water bodies, and sediments, and determines the simulated pollutant results. The model verification module... The verification module is used to divide environmental monitoring data into calibration and validation sets, and evaluate the model performance based on the calibration and validation sets after parameter calibration by the model evaluation unit. The scenario analysis module is used to perform a fully coupled simulation of the risk of water body blackening and odor return corresponding to various preset urban scenarios based on the pollutant simulation results when the model performance evaluation is passed, and determine the target risk assessment results. The embodiments of the present invention can regard the material migration and transformation process of land pipelines, land-water interface, air-water interface and mud-water interface as an organic whole. By establishing an interface coupling mathematical model and nonlinear feedback mechanism, the accuracy of the assessment of the risk of urban water body blackening and odor return can be significantly improved.

[0015] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0016] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. Attached Figure Description

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the structure of an urban water body blackening and odor risk assessment system based on multi-interface coupling, provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of the specific structure of a risk assessment system for urban water bodies that revert to blackening and odor based on multi-interface coupling, provided in an embodiment of the present invention. Figure 3A flowchart illustrating a method for assessing the risk of urban water bodies turning black and smelly based on multi-interface coupling, provided in an embodiment of the present invention. Figure 4 This is a schematic diagram of the structure of a server provided in an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Currently, in the field of urban water environment management, the problem of black and odorous water bodies remains an urgent environmental challenge. Research on the migration and transformation processes of black and odorous substances in urban water bodies mainly focuses on the simulation and prediction of single interfaces. For example, in the study of pollutant migration mechanisms, diffusion gradient thin film technology has revealed that the water-sediment interface is a key region for the migration of pollutants such as NH4+-N and PO43-, and its spatial heterogeneity provides an important basis for interface model construction. For the material exchange at the water-sediment interface, the analysis of microbial community characteristics has confirmed the significant impact of microbial-driven effects on pollutant transformation at this interface, and a sediment resuspension and release model has been established. Modeling the gas-water exchange process of volatile substances, through the study of organic pollutant transformation mechanisms, has clarified the key role of sulfur-containing amino acid degradation products in the formation of odorous gases, providing a chemical transformation theoretical basis for gas-water exchange models.

[0021] While existing research has deepened our understanding of the formation mechanisms of black and odorous water bodies, current studies primarily focus on single-interface simulations, lacking a systematic consideration of multi-interface coupling effects. In existing technologies, single-interface simulation methods based on water quality models mainly consider material transformation processes within the water body; land-based pollution simulation methods, primarily based on source apportionment, focus on surface runoff pollution; and mud-water interface models targeting sediment release mainly simulate the diffusion and release processes of pollutants in sediments. All of these approaches explore the problem of black and odorous water bodies from different perspectives, but due to the lack of systematic research on multi-interface coupling effects, accurate simulations are difficult to achieve. To accurately simulate and predict the migration and transformation patterns of black and odorous substances in urban water bodies, this invention provides a multi-interface coupling-based risk assessment system and method for urban water body blackening and odor recurrence. This system constructs a multi-interface coupling model encompassing six key processes: land-based pipelines, land-water interface, air-water interface, mud-water interface, water body material accumulation, and sediment material accumulation. By establishing material transport equations for each interface and water body material accumulation equations, the system achieves dynamic prediction of the migration and transformation processes of black and odorous substances in urban water bodies, thereby providing decision support for the prevention and control of black and odorous water bodies and significantly improving the accuracy of risk assessment for urban water body blackening and odor recurrence.

[0022] To facilitate understanding of this embodiment, a detailed description of the risk assessment method for urban water body blackening and odor recurrence based on multi-interface coupling disclosed in this invention will be provided first. This method is applied to an urban water body blackening and odor recurrence risk assessment system based on multi-interface coupling. To facilitate understanding of the urban water body blackening and odor recurrence risk assessment system based on multi-interface coupling, this invention provides a structural schematic diagram of such a system, as shown below. Figure 1 As shown, the system includes: parameter acquisition module, core function module, model verification module and scenario analysis module. The system breaks through by modeling six key links as an organic whole: (1) land pipeline interface, which mainly describes the accumulation, degradation and biotransformation process of pollutants in the pipeline network; (2) land-water interface, which characterizes the material exchange flux between land and water under rainfall conditions; (3) air-water interface, which reflects the volatilization, dissolution and diffusion process between water and atmosphere; (4) mud-water interface, which depicts the adsorption, desorption and diffusion migration between bottom sediment and overlying water. Through innovative interface coupling mechanism and nonlinear feedback mechanism, the system realizes accurate simulation of the formation process of black and odorous water bodies; (5) material accumulation in water bodies and (6) material accumulation in sediments.

[0023] To this end, this invention proposes using Vensim to construct a comprehensive system dynamics model. This model simulates the behavior of black and odorous substances in six key stages: land-based pipelines, land-water interface, air-water interface, mud-water interface, accumulation in water bodies, and accumulation in sediments. This model not only helps to deepen our understanding of the formation mechanism of black and odorous water bodies but also provides a powerful decision support tool for urban water environment management. The system adopts a modular design, comprising six core functional modules and three support modules. The core modules are responsible for simulating material transport at different interfaces, while the support modules ensure the reliable operation and verification of the system. See [link to relevant documentation]. Figure 2 The diagram shows a specific structure of a risk assessment system for urban water bodies that revert to black and odorous conditions based on multi-interface coupling. The system comprises six core functional modules: a land-water interface module, a land-water interface module, a gas-water interface module, a mud-water interface module, a material accumulation module in water bodies, and a material accumulation module in sediments. The system also includes three supporting modules: a parameter acquisition module, a model verification module, and a scenario analysis module.

[0024] The parameter acquisition module is used to acquire environmental monitoring data collected by the sensor. This environmental monitoring data includes constant parameters and dynamic environmental factors. In other words, the parameter acquisition and environmental factor monitoring system of this invention is divided into two parts: constant parameter acquisition and dynamic environmental factor monitoring. The model parameter table is shown in Table 1 below, and the model variable table is shown in Table 2 below. Table 1 Model Parameter Table

[0025] Table 2 Model Variables Table

[0026] The core functional modules are used to simulate the exchange flux of black and odorous substances in land pipelines, land-water interfaces, air-water interfaces, and mud-water interfaces, as well as the material accumulation information in land pipelines, water bodies, and sediments, based on environmental monitoring data and the system dynamics model, to determine the pollutant simulation results. In one implementation, the six core functional modules (land pipeline module, land-water interface module, air-water interface module, mud-water interface module, material accumulation module in water bodies, and material accumulation module in sediments) are analyzed, specifically including the following (1) to (6): (1) Land Pipeline Module, wherein the land pipeline module is used to analyze and process the accumulation information of organic matter, sulfide, and ammonium nitrogen in land pipelines based on the analysis model of material accumulation in land pipelines, so as to determine the dynamic change information of black and odorous substances in land pipelines. Specifically, in the generalization model, only organic matter in land pipelines is considered. ), sulfides ) and ammonium nitrogen ( The accumulation process of three key components is assumed to have a constant microbial concentration, and the environmental factor dependence of the reaction rate is generalized. The generalized differential equations for the accumulation of material in terrestrial conduits include the following (a) to (c): (a) Accumulation of organic matter in land-based pipelines ( ):

[0027] (b) Sulfide accumulation in land-based pipelines ):

[0028] (c) Accumulation of ammonium nitrogen in land-based pipelines ( ):

[0029] The component concentration includes the concentration of organic matter in the pipeline ( ), sulfide concentration ( ) and ammonium nitrogen concentration ( The units are all milligrams per liter (mg / L); the input and output rates of pollutants are respectively expressed in milligrams per liter (mg / L). , , and , , The data is expressed in milligrams per liter per hour (mg / L·h), and the key reaction rate coefficients include the temperature-dependent (T) anaerobic fermentation rate coefficients for organic matter. and sulfide oxidation rate coefficient dependent on dissolved oxygen (DO) All units are per hour (1 / h). Maximum microbial degradation rates include those of aerobic heterotrophic bacteria. sulfate-reducing bacteria and sulfide-oxidizing bacteria The maximum degradation rate is temperature-dependent and expressed in milligrams per liter per hour (mg / L·h). The half-saturation constant includes that of aerobic heterotrophic bacteria. sulfate-reducing bacteria and sulfide-oxidizing bacteria The half-saturation constants are expressed in milligrams per liter (mg / L). Microbial concentrations include aerobic heterotrophic bacteria. sulfate-reducing bacteria and sulfide-oxidizing bacteria The concentrations are all assumed to be constants and the unit is milligrams per liter (mg / L). Yield coefficients include those for the production of sulfides from organic matter by sulfate-reducing bacteria. The yield coefficient of ammonium nitrogen produced by the ammoniation of organic matter (mgS2- / mgOM) and other factors. (mgNH4+ / mgOM). Environmental factors include temperature (T, in degrees Celsius °C) and dissolved oxygen (DO, in milligrams per liter (mg / L)).

[0030] In other words, the above set of formulas describes the dynamic changes of key black and odorous substances in land pipelines. The generalized model assumes that the microbial concentration is constant and generalizes the dependence of the reaction rate on environmental factors, mainly considering the effects of temperature and dissolved oxygen, while secondary processes such as biofilm feedback are ignored.

[0031] (2) Land-water interface module, wherein the land-water interface module is used to analyze and process the organic matter exchange information, sulfide exchange information and ammonium nitrogen exchange information at the land-water interface based on the pollutant concentration difference between the land and water bodies, and to determine the exchange flux of dissolved pollutants at the land-water interface. Specifically, in the generalization model, the material exchange flux at the land-water interface only considers organic matter ( ), sulfides ) and ammonium nitrogen ( Assuming that the three components have the same mass transfer coefficient and environmental factor influence function, the generalized set of land-water interface mass exchange flux equations includes the following (a) to (c): (a) Organic matter exchange at the land-water interface ):

[0032] (b) Sulfide exchange at the land-water interface ):

[0033] (c) Ammonium nitrogen exchange at the land-water interface ):

[0034] Among them, the flux of three components (unit: mg / m²·h) is mainly involved in the material exchange process at the land-water interface: organic matter flux at the land-water interface. sulfide flux and ammonium nitrogen flux These fluxes are influenced by the concentrations of corresponding pollutants in terrestrial and aquatic bodies. Terrestrial pollutant concentrations (in mg / L) include terrestrial organic matter concentrations. Sulfide concentration and ammonium nitrogen concentration The concentration of pollutants in water bodies (in mg / L) includes the concentration of organic matter in the water. Sulfide concentration and ammonium nitrogen concentration Mass transport processes are governed by the universal mass transfer coefficient at the land-water interface. (Unit: m / h) Controlled, this coefficient mainly depends on rainfall intensity. (Unit: mm / h) This is a key environmental factor.

[0035] In other words, the above set of formulas describes the exchange flux of dissolved pollutants at the land-water interface, driven by the concentration difference between land and water. The generalized model assumes that different components have the same mass transfer coefficient, and that the mass transfer coefficient is only related to rainfall intensity. The effects of temperature and dissolved oxygen, as well as dynamic hysteresis effects, are ignored.

[0036] (3) Gas-water interface module, wherein the gas-water interface module is used to analyze and process the sulfide exchange information and ammonium nitrogen exchange information at the gas-water interface based on the pollutant concentration difference between the gas and water bodies and in combination with the Henry's constant to balance the volatile state, and to determine the exchange flux of pollutants at the gas-water interface. Specifically, in the generalization model, the gas-water interface material exchange flux mainly considers sulfides ( ) and ammonium nitrogen ( The exchange of two key gaseous pollutants, assuming that their mass transfer coefficients are the same, is represented by the following generalized gas-water interface mass exchange flux equations (a) to (b): (a) Sulfide exchange at the gas-water interface ):

[0037] (b) Ammonium nitrogen exchange at the gas-water interface ):

[0038] In the gas-water interface mass exchange process, the fluxes of two main components are sulfides and ammonium nitrogen. and The unit is milligrams per square meter per hour (mg / m²·h). These fluxes are affected by the concentration of the corresponding pollutants in the water body. and (Unit: mg / L) and concentration of pollutants in the atmosphere and The influence of (unit: mg / m³) is that atmospheric sulfides and ammonia nitrogen mainly exist in the form of H₂S and NH₃, and the mass transport process is determined by the universal mass transfer coefficient at the air-water interface. (Unit: m / h) Controlled, this coefficient mainly depends on wind speed. (Unit: m / s), in addition, the Henry's constant for sulfides and ammonium nitrogen. and (dimensionless) varies with temperature The change (in °C) is a key parameter describing the distribution equilibrium of these substances in the gas and liquid phases.

[0039] In other words, the above set of formulas describes the gas exchange flux of sulfides and ammonium nitrogen at the gas-water interface, driven by the concentration difference between the gas and water phases, and considers the influence of the Henry's constant on the volatilization equilibrium. The generalized model assumes that sulfides and ammonium nitrogen have the same mass transfer coefficient, and that the mass transfer coefficient is only related to wind speed. Secondary processes such as vertical diffusion are neglected. The component specificity and temperature dependence of the Henry's constant are preserved.

[0040] (4) Mud-water interface module, wherein the mud-water interface module is used to analyze and process the organic matter exchange information, sulfide exchange information and ammonium nitrogen exchange information at the air-water interface based on the pollutant concentration difference between sediment pore water and water body and the preset distribution coefficient, and to determine the exchange flux of dissolved pollutants at the mud-water interface. Specifically, in the generalization model, the mud-water interface material exchange flux only considers organic matter ( ), sulfides ) and ammonium nitrogen ( Assuming that the three components have the same mass transfer coefficient and diffusion is ignored, the generalized set of mass exchange flux equations at the mud-water interface includes the following (a) to (c): (a) Organic matter exchange at the mud-water interface ):

[0041] (b) Sulfide exchange at the mud-water interface ):

[0042] (c) Ammonium nitrogen exchange at the mud-water interface ):

[0043] In the mass exchange process at the mud-water interface, the flux mainly includes organic matter flux. sulfide flux and ammonium nitrogen flux All values ​​are milligrams per square meter per hour (mg / m²·h). Contaminant concentrations in sediment pore water include organic matter concentrations. Sulfide concentration and ammonium nitrogen concentration All values ​​are in milligrams per liter (mg / L). The corresponding concentrations of pollutants in water bodies include the concentration of organic matter. Sulfide concentration and ammonium nitrogen concentration The unit is also milligrams per liter (mg / L). Mass transport processes are determined by the universal mass transfer coefficient at the mud-water interface. Control, measured in meters per hour (m / h), this coefficient depends primarily on dissolved oxygen (DO, measured in milligrams per liter) and redox potential (…). (Units are millivolts or volts). In addition, the distribution coefficients of each component... , and (Unit: liters per kilogram, L / kg) is generalized to a constant, but its component specificity is preserved. Dissolved oxygen (DO) and redox potential (DO) are environmental factors. () is a key parameter that affects the material exchange process.

[0044] In other words, the above set of formulas describes the exchange flux of dissolved pollutants at the mud-water interface, driven by the concentration difference between sediment pore water and the water body, as well as the partition coefficient. The generalized model assumes that different components have the same mass transfer coefficient, and that the mass transfer coefficient is mainly related to dissolved oxygen and redox potential. The effects of other factors such as temperature, pH, microbial activity, and internal sediment diffusion are neglected. The partition coefficient is generalized to a constant, but its component specificity is preserved.

[0045] (5) Module for the accumulation of substances in water bodies, wherein the module for the accumulation of substances in water bodies is used to analyze and process the accumulation information of organic matter, sulfide, and ammonium nitrogen in water bodies according to the analytical model of the accumulation of substances in water bodies, and to determine the dynamic change information of black and odorous substances in water bodies. Specifically, in the generalization model, the accumulation process of substances in water bodies only considers organic matter ( ), sulfides ) and ammonium nitrogen ( The accumulation and transformation of three key components. Microbial concentration is assumed to be constant, and the environmental factor dependence of the reaction rate is generalized. The water quality recovery elasticity function is neglected. The generalized differential equations for water body material accumulation include the following (a) to (c): (a) Accumulation of organic matter in water bodies ):

[0046] (b) Accumulation of sulfides in water bodies ):

[0047] (c) Accumulation of ammonium nitrogen in water bodies ):

[0048] In the process of water substance accumulation, the component concentration mainly includes the concentration of organic matter in the water. , water sulfide concentration and the concentration of ammonium nitrogen in water (Units are all mg / L). Interfacial flux includes the land-water interfacial flux from the generalized formula in step (2) above. , and The gas-water interface flux from the generalized formula in step (3) above , and (Among them, the generalized formula in step (3) above may only contain sulfide and ammonium nitrogen fluxes, and the organic flux may be 0), and the mud-water interface flux from the generalized formula in step (3) above. , and (Units are all mg / m²·h). These interfacial fluxes act on the land-water interface area, respectively. air-water interface area Mud-water interface area (All units are m²)

[0049] Regarding pipeline input, this includes the concentrations of pollutants in each component of the pipeline from the generalized formula derived from step (1) above. , and (Unit: mg / L), and pipeline drainage flow rate (Unit: m³ / h). Key reaction rate coefficients include temperature-dependent anaerobic fermentation rate coefficients for organic matter. and the sulfide oxidation rate coefficient dependent on dissolved oxygen (Units are all 1 / h). Maximum microbial degradation rates include temperature-dependent maximum degradation rates of aerobic heterotrophic bacteria in water. Maximum degradation rate of sulfate-reducing bacteria in water Maximum degradation rate of sulfide-oxidizing bacteria in water (All units are mg / L·h).

[0050] In addition, the corresponding half-saturation constants include the half-saturation constants of aerobic heterotrophic bacteria in water. Half-saturation constant of sulfate-reducing bacteria in water Half-saturation constant of sulfide-oxidizing bacteria in water (Units are all mg / L). The concentration of microorganisms in the water is generalized to a constant, including the concentration of aerobic heterotrophic bacteria. Concentration of sulfate-reducing bacteria in water and the concentration of sulfide-oxidizing bacteria in water (Units are all mg / L). Yield coefficients include the yield coefficients for sulfate-reducing bacteria degrading organic matter to produce sulfides. The yield coefficient of ammonium nitrogen produced by the ammoniation of organic matter (mgS2- / mgOM) and other factors. (mgNH4+ / mgOM). Environmental factors include water volume. (m³), temperature (°C) and dissolved oxygen (mg / L).

[0051] In other words, the above set of formulas describes the dynamic changes of organic matter, sulfides and ammonium nitrogen in water bodies, which are jointly affected by the material exchange at the land-water, air-water and mud-water interfaces, pipeline input, and biochemical reactions within the water body. The generalized model assumes that the concentration of microorganisms in the water body is constant and generalizes the environmental factor dependence of the reaction rate. Secondary mechanisms such as water quality recovery elasticity are ignored. The entire model system is coupled with each other through the interface flux term, forming a generalized coupled model of urban water body blackening and odor return.

[0052] (6) Sediment material accumulation module, wherein the sediment material accumulation module is used to analyze and process the organic matter accumulation information, sulfide accumulation information and ammonium nitrogen accumulation information in the sediment according to the sediment material accumulation analysis model, and determine the dynamic change information of black and odorous substances in the sediment. Specifically, when simplifying the model, the sediment material accumulation process only considers organic matter ( ), sulfides ( ) and ammonium nitrogen ( The accumulation and transformation of three key components, with the microbial concentration assumed to be constant and the environmental factor dependence of the reaction rate simplified, result in the following simplified differential equations for sediment accumulation: (a) to (c) (a) Accumulation of organic matter in sediments ):

[0053] (b) Accumulation of sulfides in sediments ):

[0054] (c) Accumulation of ammonium nitrogen in sediments ):

[0055] Among them, the component concentration includes the concentration of organic matter in the sediment ( ), concentration of sulfides in sediments ( ) and the concentration of ammonium nitrogen in sediments ( The units are all milligrams per liter (mg / L). , and It is the mud-water interface flux (in mg / m²·h) from the generalized formula in step (4) above. This is the thickness of the active sediment layer (in meters), used to convert interfacial flux into the rate of concentration change in the sediment. Key reaction rate coefficients include temperature-dependent (T) sediment organic matter anaerobic fermentation rate coefficients. and sediment sulfide oxidation rate coefficients dependent on dissolved oxygen (DO) All units are per hour (1 / h). The maximum degradation rate of microorganisms includes aerobic heterotrophic bacteria in the sediment. Sulfate-reducing bacteria in sediments and sediment sulfide oxidizing bacteria The maximum degradation rate is temperature-dependent and expressed in milligrams per liter per hour (mg / L·h). The half-saturation constant includes the aerobic heterotrophic bacteria in the sediment. Sulfate-reducing bacteria in sediments and sediment sulfide oxidizing bacteria The half-saturation constants are all expressed in milligrams per liter (mg / L). Microbial concentrations include aerobic heterotrophic bacteria from the sediment. Sulfate-reducing bacteria in sediments and sediment sulfide oxidizing bacteria The concentrations are all assumed to be constants and the unit is milligrams per liter (mg / L). Yield coefficients include those for the production of sulfides from organic matter by sulfate-reducing bacteria. The yield coefficient of ammonium nitrogen produced by the ammoniation of organic matter (mgS2- / mgOM) and other factors. (mgNH4+ / mgOM). Environmental factors include temperature (T, in degrees Celsius °C) and dissolved oxygen (DO, in milligrams per liter mg / L), which are the same as those in water bodies.

[0056] In other words, the above set of formulas describes the dynamic changes of key black and odorous substances in sediments, which are jointly influenced by the exchange of substances at the mud-water interface and the biochemical reactions within the sediments. The simplified model assumes that the sediment microbial concentration is constant and simplifies the dependence of reaction rates on environmental factors. Minor processes such as sediment diffusion are ignored. The generalized formulas from step (4) and step (6) above are coupled through the mud-water interface flux term.

[0057] The model validation module is used to divide environmental monitoring data into calibration and validation sets, and to evaluate model performance based on the calibration and validation sets after parameter calibration by the model evaluation unit. The model validation module includes: a dataset partitioning unit for dividing data into calibration and validation sets; a parameter optimization unit for optimizing model parameters; and a model evaluation unit for evaluating model performance.

[0058] The scenario analysis module is used to perform a fully coupled simulation of the risk of water bodies turning black and smelly again under various preset urban scenarios based on the pollutant simulation results when the model performance evaluation is passed, and to determine the target risk assessment results. Among them, when assessing the risk evolution law of urban water bodies turning black and smelly again under different conditions, it mainly includes the following (1) to (3): (1) Rainfall scenario analysis: This system systematically studies the impact mechanism of rainfall on water quality, focusing on the quantitative effect of rainfall intensity in the range of 0-50 mm / h on the input of pollutants at the land-water interface. At the same time, it compares and studies the differences in water quality changes under continuous rainfall and intermittent rainfall conditions. By establishing a quantitative assessment system for the initial rainwater flushing effect, and combining the accumulation and flushing dynamics of pollutants during the rainfall-runoff process, the system realizes the simulation and analysis of the entire process of water quality changes under rainfall conditions.

[0059] (2) Scenario analysis of engineering measures: The scenario analysis of engineering measures in this system is mainly carried out in depth from two aspects: pipeline system renovation and sediment treatment. In terms of pipeline system renovation, the focus is on evaluating the impact mechanism of engineering measures such as improving the water flow capacity of the pipeline and dredging pipeline sediments on the migration and transformation process of pollutants. In terms of sediment treatment, the optimization strategy of sediment dredging depth is systematically studied, the application effect of in-situ remediation technology is analyzed, and the quantitative impact of various measures, including ecological restoration, on the material exchange process of the mud-water interface is evaluated, so as to provide a scientific basis for decision-making in engineering practice.

[0060] (3) Scenario analysis of environmental factors: The scenario analysis of environmental factors in this system mainly focuses on two key aspects: temperature and hydrological conditions. In terms of temperature changes, the system focuses on the impact mechanism of temperature changes in the range of 5-35℃ on various interface processes, including the effects of increased microbial activity and intensified volatilization at the air-water interface caused by temperature rise. In terms of changes in hydrological conditions, the system analyzes in depth the impact mechanism of flow velocity changes and water level fluctuations on the exchange of interfacial materials, thereby achieving a systematic assessment of the impact of hydrological factors.

[0061] based on Figure 1 The diagram shows a structural schematic of a risk assessment system for urban water body blackening and odor recurrence based on multi-interface coupling. Figure 2 The diagram shows a specific structural schematic of an urban water body blackening and odor recurrence risk assessment system based on multi-interface coupling. This invention provides a detailed description of the urban water body blackening and odor recurrence risk assessment method based on multi-interface coupling. (See also...) Figure 3 The diagram shows a flowchart of a method for assessing the risk of urban water bodies turning black and smelly again based on multi-interface coupling. The method mainly includes the following steps S302 to S306: Step S302: Obtain environmental monitoring data, which includes constant parameters and dynamic environmental factors.

[0062] Step S304 involves using the land-based pipeline module, land-water interface module, air-water interface module, mud-water interface module, water body material accumulation module, and sediment material accumulation module to analyze and process constant parameters and dynamic environmental factors, determining the pollutant simulation results. These results include: dynamic changes in black and odorous substances in the land-based pipeline; exchange fluxes of dissolved pollutants at the land-water interface; exchange fluxes of pollutants at the air-water interface; exchange fluxes of dissolved pollutants at the mud-water interface; dynamic changes in black and odorous substances in the water body; and dynamic changes in black and odorous substances in the sediment. In one embodiment, the fully coupled simulation of the land-based pipeline, land-water interface, air-water interface, and mud-water interface, based on the system integration effect, overcomes the limitations of traditional single-interface models. Furthermore, by establishing a unified mathematical framework, the material transport and interactions between each interface are systematically described, making the prediction results more consistent with the actual migration and transformation process of black and odorous substances in the water body.

[0063] Furthermore, by constructing a model using system dynamics methods, it is possible to simulate the dynamic changes in the concentration of black and odorous substances in water bodies. By establishing material transport equations for each interface, material accumulation equations for water bodies, and material accumulation equations for sediments, the system can accurately reflect the impact of changes in external conditions (such as rainfall and sewage discharge) on water quality. In particular, it can demonstrate excellent dynamic response performance when predicting sudden pollution events or assessing the effectiveness of treatment measures.

[0064] Step S306: Based on the pollutant simulation results, a fully coupled simulation is performed on the risk of water bodies turning black and smelly again corresponding to various preset urban scenarios to determine the target risk assessment results. In one implementation, scenario analysis is an important technology to support decision-making. By integrating the scenario analysis module, the control effect of water body blackness and odor under different management strategies can be simulated. By adjusting the model parameters, the effects of various treatment measures (such as source control and interception of pollution, bottom sediment dredging, oxygenation, etc.) can be predicted, providing a scientific basis for management decisions.

[0065] Furthermore, for step S304 above, a nonlinear mathematical model system considering the interface coupling effect was constructed, as detailed in (1) to (6) below: (1) Material accumulation in land-based pipelines:

[0066] in, Represents the concentration vector of various pollutants in the pipeline (mg / L) For time (h), For the input rate vectors (mg / L·h) of various pollutants, For the output rate vectors (mg / L·h) of various pollutants, This is a temperature- and dissolved oxygen-dependent degradation coefficient matrix, including: anaerobic fermentation rate coefficients of organic matter. and sulfide oxidation rate coefficient ( ), The maximum degradation rate for the i-th type of microorganisms includes: aerobic heterotrophic bacteria. sulfate-reducing bacteria and sulfide-oxidizing bacteria ( ), The corresponding half-saturation constant (mg / L) For the concentration of various microorganisms, including: , and (mg / L).

[0067] (2) Material exchange at the land-water interface:

[0068] in, Represents the flux vectors of various pollutants at the land-water interface: (mg / m²·h) in, The mass transfer coefficient (m / h) Rainfall intensity (mm / h), Represents the concentration vector of various pollutants in the land area (mg / L) Vector representing the concentration of various pollutants in water bodies (mg / L).

[0069] (3) Material exchange at the air-water interface:

[0070] in, Represents the flux vectors of various pollutants at the air-water interface. (mg / m²·h) The mass transfer coefficient (m / h) Wind speed (m / s) Represents the Henry's constant vector of each component (dimensionless) Temperature (°C) Vector representing the concentration of various pollutants in water bodies (mg / L) Vector representing the concentration of various pollutants in the atmosphere (mg / m³).

[0071] (4) Material exchange at the mud-water interface:

[0072] in, Represents the flux vectors of various pollutants at the mud-water interface. (mg / m²·h) The mass transfer coefficient (m / h) depends primarily on dissolved oxygen (DO) and redox potential ( ). ), Vector representing the concentration of various pollutants in sediment pore water (mg / L) Vector representing the distribution coefficients of each component (L / kg) Vector representing the concentration of various pollutants in water bodies (mg / L).

[0073] (5) Accumulation of substances in water bodies:

[0074] in, Vector representing the concentration of various pollutants in water bodies (mg / L) The volume of water (m³) , , These are the flux vectors (mg / m²·h) at the land-water, air-water, and mud-water interfaces, respectively. , , These represent the interface areas (m²) of land-water, air-water, and mud-water, respectively. The drainage flow rate of the pipeline (m³ / h) This represents the vector of pollutant concentration (mg / L) in the pipeline. This is a temperature-dependent degradation coefficient matrix. The maximum degradation rate of the i-th type of microorganisms (including aerobic heterotrophic bacteria, sulfate-reducing bacteria, and sulfide-oxidizing bacteria) ), The corresponding half-saturation constant (mg / L) This represents the concentration (mg / L) of various microorganisms in the water.

[0075] (6) Accumulation of substances in sediments: To simplify the model, the material accumulation process in sediments only considers the accumulation and transformation of various key pollutant components, the microbial concentration is assumed to be constant, and the environmental factor dependence of the reaction rate is simplified. The following is the simplified general differential equation for material accumulation in sediments:

[0076] in, This represents a vector (mg / L) of various pollutant concentrations in the sediment. This represents the flux vector (mg / m²·h) of various pollutants at the mud-water interface. It is the thickness (m) of the active sediment layer. This represents the rate vector of biochemical reactions in the sediment.

[0077] This invention also provides an implementation method for model calibration and validation. The model validation module includes: a dataset partitioning unit, a parameter optimization unit, and a model evaluation unit, as detailed in (1) to (3) below: (1) Data set partitioning unit: All available data are divided into calibration set and validation set in a ratio of 7:3. The calibration set is mainly used for optimizing and adjusting model parameters and sensitivity analysis, while the validation set is used to independently evaluate the predictive ability and stability of the model to ensure the reliability and practicality of the model.

[0078] (2) Parameter optimization unit: First, historical monitoring data is systematically collected as the basis for model calibration, including water quality monitoring data (such as DO, pH, EC, etc.), meteorological data (such as rainfall, wind speed, temperature, etc.), and pollutant concentration data at each interface ( , , , Based on this, parameters are calibrated to ensure the scientific validity and reliability of the model parameters, including hydrological parameters such as flow rate and water level.

[0079] (3) Model evaluation unit: The model performance is evaluated using an independent validation dataset and multi-level statistical indicators are used for evaluation. Root Mean Square Error (RMSE):

[0080] Coefficient of determination (R²):

[0081] Nash-Sutcliffe efficiency coefficient (NSE):

[0082] Relative error (RE):

[0083] in, For the observed values, is the predicted value, and These are the average values ​​of the observed and predicted values, respectively.

[0084] In summary, this invention unifies the mass transport processes of land-based pipelines, land-water interfaces, air-water interfaces, and mud-water interfaces into a single mathematical framework through multi-interface coupling modeling technology. Quantitative coupling of fluxes at each interface is achieved through the accumulation equations of the central processing module. Simultaneously, a complete set of interface mass transfer equations is established, ensuring the model has clear physical meaning. A nonlinear feedback mechanism is used to consider the nonlinear influence of environmental factors and describe the kinetic characteristics of biodegradation, simulating the dynamic changes in interface fluxes to reflect the system's adaptive characteristics. Finally, through scenario analysis, evaluation methods for different management strategies are established, and impact assessment modules for rainfall, hydrology, temperature, and engineering measures are developed. A multi-scenario comparative analysis function is also designed. These technical means provide a scientific basis for management decisions.

[0085] This invention provides a server, specifically, the server includes a processor and a storage device; the storage device stores a computer program, which, when run by the processor, executes the method described in any of the above embodiments.

[0086] Figure 4 This is a schematic diagram of the structure of a server provided in an embodiment of the present invention. The server 100 includes: a processor 40, a memory 41, a bus 42 and a communication interface 43. The processor 40, the communication interface 43 and the memory 41 are connected through the bus 42. The processor 40 is used to execute executable modules, such as computer programs, stored in the memory 41.

[0087] The memory 41 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 43 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc.

[0088] Bus 42 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0089] The memory 41 is used to store programs. After receiving an execution instruction, the processor 40 executes the program. The method executed by the device for defining the flow process disclosed in any of the foregoing embodiments of the present invention can be applied to the processor 40 or implemented by the processor 40.

[0090] Processor 40 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 40 or by instructions in software form. Processor 40 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 41, and the processor 40 reads the information from memory 41 and, in conjunction with its hardware, completes the steps of the above method.

[0091] The computer program product of the readable storage medium provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the foregoing method embodiments. For specific implementation, please refer to the foregoing method embodiments, which will not be repeated here.

[0092] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0093] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A risk assessment system for urban water bodies turning black and smelly again based on multi-interface coupling, characterized in that, The system includes: a parameter acquisition module, a core function module, a model validation module, and a scenario analysis module; wherein, The parameter acquisition module is used to acquire environmental monitoring data collected by the sensor, wherein the environmental monitoring data includes: constant parameters and dynamic environmental factors; The core functional module is used to simulate the exchange flux of black and odorous substances at the land-water interface, air-water interface, and mud-water interface, as well as the material accumulation information in land pipelines, water bodies, and sediments, based on the environmental monitoring data through the system dynamics model, and to determine the pollutant simulation results. The model validation module is used to divide the environmental monitoring data into a calibration set and a validation set, and to evaluate the model performance based on the calibration set and the validation set after parameter calibration by the model evaluation unit. The scenario analysis module is used to perform a fully coupled simulation of the risk of water bodies turning black and smelly again for each preset urban scenario based on the pollutant simulation results when the model performance evaluation is passed, and to determine the target risk assessment results.

2. The urban water body blackening and odor recurrence risk assessment system based on multi-interface coupling according to claim 1, characterized in that, The core functional modules include: a land-based pipeline module; wherein... The land pipeline module is used to analyze and process the accumulation information of organic matter, sulfides, and ammonium nitrogen in the land pipeline according to the analysis model of material accumulation in the land pipeline, so as to determine the dynamic change information of black and odorous substances in the land pipeline.

3. The risk assessment system for urban water body blackening and odor recurrence based on multi-interface coupling according to claim 1, characterized in that, The core functional modules include: a land-water interface module; wherein... The land-water interface module is used to analyze and process the exchange information of organic matter, sulfide, and ammonium nitrogen at the land-water interface based on the pollutant concentration difference between land and water, and to determine the exchange flux of dissolved pollutants at the land-water interface.

4. The risk assessment system for urban water body blackening and odor recurrence based on multi-interface coupling according to claim 1, characterized in that, The core functional modules include: an air-water interface module; wherein... The gas-water interface module is used to analyze and process the sulfide exchange information and ammonium nitrogen exchange information at the gas-water interface based on the pollutant concentration difference between the gas and water, and in combination with the Henry's constant to balance the volatile state, so as to determine the exchange flux of pollutants at the gas-water interface.

5. The urban water body blackening and odor recurrence risk assessment system based on multi-interface coupling according to claim 1, characterized in that, The core functional modules include: a mud-water interface module; wherein... The mud-water interface module is used to analyze and process the organic matter exchange information, sulfide exchange information, and ammonium nitrogen exchange information at the air-water interface based on the pollutant concentration difference between sediment pore water and water body, as well as a preset distribution coefficient, to determine the exchange flux of dissolved pollutants at the mud-water interface.

6. The risk assessment system for urban water body blackening and odor recurrence based on multi-interface coupling according to claim 1, characterized in that, The core functional modules include: a module for the accumulation of substances in water; wherein... The water body material accumulation module is used to analyze and process the organic matter accumulation information, sulfide accumulation information and ammonium nitrogen accumulation information in the water body according to the water body material accumulation analysis model, and determine the dynamic change information of black and odorous substances in the water body.

7. The risk assessment system for urban water body blackening and odor recurrence based on multi-interface coupling according to claim 1, characterized in that, The core functional modules include: a module for the accumulation of substances in sediments; wherein... The sediment accumulation module is used to analyze and process the accumulation information of organic matter, sulfide, and ammonium nitrogen in sediments according to the sediment accumulation analysis model, and to determine the dynamic change information of black and odorous substances in sediments.

8. A method for assessing the risk of urban water bodies turning black and smelly again based on multi-interface coupling, characterized in that, The method is applied to a risk assessment system for the re-blackening and re-odorization of urban water bodies based on multi-interface coupling. The method includes: Acquire environmental monitoring data, wherein the environmental monitoring data includes: constant parameters and dynamic environmental factors; The constant parameters and dynamic environmental factors are analyzed and processed using the land pipeline module, land-water interface module, air-water interface module, mud-water interface module, water body material accumulation module, and sediment material accumulation module, respectively, to determine the pollutant simulation results. The pollutant simulation results include: dynamic change information of black and odorous substances in land pipelines, exchange flux of dissolved pollutants at the land-water interface, exchange flux of pollutants at the air-water interface, exchange flux of dissolved pollutants at the mud-water interface, dynamic change information of black and odorous substances in water bodies, and dynamic change information of black and odorous substances in sediments. Based on the pollutant simulation results, a fully coupled simulation is performed on the risk of water bodies turning black and smelly again for each preset urban scenario to determine the target risk assessment results.

9. A server, characterized in that, The method includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, the processor executing the computer-executable instructions to implement the method of claim 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when invoked and executed by a processor, cause the processor to implement the method of claim 8.

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