Risk assessment system and method for blackening and stink of urban water body based on multi-interface coupling

Abstract

The application provides a kind of urban water body blackening and malodorous risk assessment system and method based on multi-interface coupling, related to the technical field of water environment monitoring and evaluation, parameter acquisition module is used to obtain the environmental monitoring data collected by sensor;Core function 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, and the substance accumulation information in the land pipeline, water body and sediment based on the environmental monitoring data through the system dynamics model, to determine the pollutant simulation result;Model verification module is used to evaluate the model performance based on the calibration set and the validation set after parameter calibration through the model evaluation unit;Scenario analysis module is used to perform full-coupling simulation of the water body blackening and malodorous risk corresponding to each preset urban scenario according to the pollutant simulation result when the model performance evaluation is passed, to determine the target risk assessment result.The application can significantly improve the accuracy of the evaluation of urban water body blackening and malodorous risk.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water environment monitoring and evaluation, and in particular to a city water body blackening and malodorous risk assessment system and method based on multi-interface coupling. BACKGROUND

[0002] In the field of city water environment management, the problem of water body blackening and malodor has been an urgent environmental problem to be solved. At present, the research on the migration and transformation process of blackening and malodorous substances in city water bodies mainly focuses on the simulation and prediction of a single interface. However, this scheme is difficult to comprehensively describe the migration and transformation rules of blackening and malodorous substances. Meanwhile, the existing models mostly use complex hydrodynamic equations, which have a large amount of calculation and are not conducive to rapid prediction and management decision-making. Moreover, the existing scheme lacks systematic consideration of the material exchange between land, water, atmosphere and sediment, and generally has the problem of interface process fragmentation. The interaction relationship between land pipes, land-water interface, air-water interface and mud-water interface is not fully considered, which makes it impossible to comprehensively reflect the migration and transformation process of substances among multiple interfaces, and the evaluation results are one-sided. In addition, the existing models mostly use steady-state or quasi-steady-state assumptions, which are difficult to simulate the dynamic influence of external factors such as rainfall on water body blackening and malodour. Especially when simulating the water quality change under sudden pollution events or extreme weather conditions, the accuracy of the prediction results is low, thereby affecting the accuracy of the city water body blackening and malodorous risk assessment. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a city water body blackening and malodorous risk assessment system and method based on multi-interface coupling, which can significantly improve the accuracy of city water body blackening and malodorous risk assessment.

[0004] In the first aspect, the present application provides a city water body blackening and malodorous risk assessment system based on multi-interface coupling. The system comprises a parameter acquisition module, a core function module, a model verification module and a scenario analysis module. The parameter acquisition module is used to acquire environmental monitoring data collected by a sensor, wherein the environmental monitoring data comprises constant parameters and dynamic environmental factors. The core function module is used to simulate the exchange flux of blackening and malodorous substances at the land pipe, land-water interface, air-water interface and mud-water interface, and the material accumulation information in the land pipe, water body and sediment based on the environmental monitoring data through a system dynamics model, and determine the pollutant simulation result. The model verification module is used to divide the environmental monitoring data into a calibration set and a verification set, and evaluate the model performance based on the parameter calibrated calibration set and verification set through a model evaluation unit. The scenario analysis module is used to perform full-coupling simulation on the water body blackening and malodorous risk corresponding to each preset city scenario according to the pollutant simulation result when the model performance evaluation is passed, and determine the target risk assessment result.

[0005] In an embodiment, the core function module comprises: a land pipeline module; wherein the land pipeline module is configured to analyze and process organic matter accumulation information, sulfide accumulation information and ammonium nitrogen accumulation information in the land pipeline according to an analysis model of land pipeline matter accumulation, so as to determine dynamic change information of black odor matter in the land pipeline.

[0006] In an embodiment, the core function module comprises: a land-water interface module; wherein the land-water interface module is configured to analyze and process organic matter exchange information, sulfide exchange information and ammonium nitrogen exchange information of the land-water interface according to a pollutant concentration difference between the land and the water body, so as to determine exchange flux of dissolved pollutants at the land-water interface.

[0007] In an embodiment, the core function module comprises: an air-water interface module; wherein the air-water interface module is configured to analyze and process sulfide exchange information and ammonium nitrogen exchange information of the air-water interface according to a pollutant concentration difference between the gas and the water body, and balance the volatile state by combining with Henry's constant, so as to determine exchange flux of pollutants at the air-water interface.

[0008] In an embodiment, the core function module comprises: a sediment-water interface module; wherein the sediment-water interface module is configured to analyze and process organic matter exchange information, sulfide exchange information and ammonium nitrogen exchange information of the sediment-water interface according to a pollutant concentration difference between the sediment pore water and the water body, and a preset distribution coefficient, so as to determine exchange flux of dissolved pollutants at the sediment-water interface.

[0009] In an embodiment, the core function module comprises: a matter accumulation module in the water body; wherein the matter accumulation module in the water body is configured to analyze and process organic matter accumulation information, sulfide accumulation information and ammonium nitrogen accumulation information in the water body according to an analysis model of water body matter accumulation, so as to determine dynamic change information of black odor matter in the water body.

[0010] In an embodiment, the core function module comprises: a matter accumulation module in the sediment; wherein the matter accumulation module in the sediment is configured to analyze and process organic matter accumulation information, sulfide accumulation information and ammonium nitrogen accumulation information in the sediment according to an analysis model of sediment matter accumulation, so as to determine dynamic change information of black odor matter in the sediment.

[0011] In a second aspect, the embodiments of the present application further provide a method for risk assessment of blackening and malodorous of urban water bodies based on multi-interface coupling, which is applied to a system for risk assessment of blackening and malodorous of urban water bodies based on multi-interface coupling, and comprises the following steps: obtaining environmental monitoring data, wherein the environmental monitoring data comprises constant parameters and dynamic environmental factors; respectively using a land pipeline module, a land-water interface module, an air-water interface module, a mud-water interface module, a substance accumulation module in water, and a substance accumulation module in sediment to analyze and process the constant parameters and the dynamic environmental factors, and determining a pollutant simulation result, wherein the pollutant simulation result comprises dynamic change information of black and odorous substances in the land pipeline, exchange flux of soluble pollutants in the land-water interface, exchange flux of pollutants in the air-water interface, exchange flux of soluble pollutants in the mud-water interface, dynamic change information of black and odorous substances in the water, and dynamic change information of black and odorous substances in the sediment; and performing full-coupling simulation on water blackening and malodorous risks corresponding to each preset urban scenario according to the pollutant simulation result, and determining a target risk assessment result.

[0012] In a third aspect, the embodiments of the present application further provide a server, comprising a processor and a memory, the memory stores computer executable instructions capable of being executed by the processor, and the processor executes the computer executable instructions to implement the method of any one of the first aspect.

[0013] In a fourth aspect, the embodiments of the present application further provide a computer readable storage medium, which stores computer executable instructions, and the computer executable instructions, when called and executed by a processor, cause the processor to implement the method of any one of the first aspect.

[0014] The embodiments of the present application bring the following beneficial effects:

[0015] The embodiment of the present application provides a kind of city water black and stink risk assessment system and method based on multi-interface coupling, system includes: parameter acquisition module, core function module, model verification module and scenario analysis module;Wherein, parameter acquisition module is used to obtain the environmental monitoring data collected by sensor, wherein, environmental monitoring data includes: constant parameter and dynamic environmental factor;Core function module is used to simulate the exchange flux of black and stink substance in land pipeline, land-water interface, air-water interface and mud-water interface, and the substance accumulation information in land pipeline, water body and sediment based on environmental monitoring data by system dynamics model, to determine pollutant simulation result;Model verification module is used to divide environmental monitoring data into calibration set and verification set, and based on the calibration set and verification set after parameter calibration, the performance of model is evaluated by model evaluation unit;Scenario analysis module is used to carry out full-coupling simulation on the water black and stink risk corresponding to each preset city scene according to pollutant simulation result when model performance evaluation passes, to determine target risk assessment result, the embodiment of the present application can regard the substance migration and transformation process of land pipeline, land-water interface, air-water interface and mud-water interface as an organic whole, by establishing interface coupling mathematical model and nonlinear feedback mechanism, to significantly improve the accuracy of the evaluation of city water black and stink risk.

[0016] Other features and advantages of the present application will be set forth in the descriptions below, and in part will become apparent to those skilled in the art from the descriptions, or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and achieved by the structures particularly pointed out in the descriptions, claims and drawings.

[0017] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the following preferred embodiments are specifically described below, and the accompanying drawings are described in detail as follows. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings needed to be used in the specific embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without creating any creative labor.

[0019] Figure 1 The structure diagram of the city water black and stink risk assessment system based on multi-interface coupling provided by the embodiment of the present application is shown in the figure.

[0020] Figure 2 The specific structure diagram of the city water black and stink risk assessment system based on multi-interface coupling provided by the embodiment of the present application is shown in the figure.

[0021] Figure 3 A flowchart of a method for evaluating the risk of blackening and stench of urban water bodies based on multi-interface coupling is provided for the embodiments of the present application.

[0022] Figure 4 A structural schematic diagram of a server is provided for the embodiments of the present application. DETAILED DESCRIPTION

[0023] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions of the present application will be described below in connection with the embodiments, obviously, the described embodiments are some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0024] At present, in the field of urban water environment management, the problem of blackening and stench of water bodies has been an urgent environmental problem to be solved. The research on the migration and transformation process of blackening and stench substances of urban water bodies mainly focuses on the simulation and prediction of a single interface. For example, in the research on the migration mechanism of pollutants, the water-sediment interface is revealed to be the key area for the migration of NH4+-N, PO43-and other pollutants by diffusion gradient thin film technology, and the spatial heterogeneity characteristics provide an important basis for the construction of interface model. For the material exchange of water-sediment interface, through the analysis of microbial community characteristics, it is confirmed that the microbial driving effect in the interface has a significant influence on the transformation of pollutants, and a model of sediment resuspension and release is established. For the gas-water exchange process of volatile substances, through the research on the transformation mechanism of organic pollutants, the key role of sulfur-containing amino acid degradation products in the formation of malodorous gas is clarified, and a chemical transformation theoretical basis for the gas-water exchange model is provided.

[0025] Although existing research deepens the understanding of the formation mechanism of black and odorous water body, the current research still mainly focuses on the simulation of a single interface, and lacks systematic consideration of the coupling effect of multiple interfaces. In the prior art, the single interface simulation method based on the water quality model mainly considers the material conversion process inside the water body, the pollution simulation method based on the pollution source analysis mainly focuses on the surface runoff pollution, and the sediment-water interface model mainly simulates the diffusion and release process of pollutants in the sediment. The above schemes explore the black and odorous problem of water body from different angles, but due to the lack of systematic research on the coupling effect of multiple interfaces, it is difficult to accurately simulate and predict the migration and transformation rule of black and odorous substances in urban water body. Based on this, the urban water body black and odorous risk assessment system and method based on multi-interface coupling provided by the embodiment of the present application construct a multi-interface coupling model including six key processes of land pipeline, land-water interface, air-water interface, sediment-water interface, material accumulation in water body and material accumulation in sediment. By establishing the material transfer equation of each interface and the material accumulation equation of water body, the dynamic prediction of the migration and transformation process of black and odorous substances in urban water body is realized, so as to provide decision support for water body black and odorous prevention and control, and significantly improve the accuracy of the evaluation of the risk of urban water body black and odorous.

[0026] In order to facilitate the understanding of the present embodiment, firstly, a kind of based on multi-interface coupling's urban water body black and odorous risk assessment method disclosed in the embodiment of the present application is introduced in detail, which is applied to the urban water body black and odorous risk assessment system based on multi-interface coupling, in order to facilitate the understanding of the urban water body black and odorous risk assessment system based on multi-interface coupling, the structure diagram of the urban water body black and odorous risk assessment system based on multi-interface coupling provided by the embodiment of the present application is as shown in Figure 1 The system includes: parameter acquisition module, core function module, model verification module and scenario analysis module, which breaks through six key links as an organic whole: (1) land pipeline interface, mainly describing the accumulation, degradation and biological transformation process of pollutants in pipe network;(2) land-water interface, representing the material exchange flux between land and water under rainfall conditions;(3) air-water interface, reflecting the volatilization, dissolution and diffusion process between water body and atmosphere;(4) sediment-water interface, depicting the adsorption and desorption and diffusion and migration between sediment and overlying water, through the innovative interface coupling mechanism and nonlinear feedback mechanism, the formation process of black and odorous water body is accurately simulated;(5) material accumulation in water body and (6) material accumulation in sediment.

[0027] To this end, the present application proposes to use Vensim to build a comprehensive system dynamics model, which is used to simulate the behavior of black-smelly substances in the six key links of land pipeline, land-water interface, air-water interface, mud-water interface, water body and sediment, which can not only help to understand the mechanism of black-smelly water formation, but also provide a powerful decision support tool for urban water environment management. The system adopts modular design, including six core function modules and three support modules. The core module is responsible for the simulation of material transfer at different interfaces, and the support module ensures the reliable operation and verification of the system. Referring to the specific structure diagram of a city water body blackening and smelly risk assessment system based on multi-interface coupling shown in Figure 2 The six core function modules include: 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. The three support modules include: parameter acquisition module, model verification module and scenario analysis module.

[0028] The parameter acquisition module is used to acquire environmental monitoring data collected by sensors, wherein the environmental monitoring data includes constant parameters and dynamic environmental factors, that is, the parameter acquisition and environmental factor monitoring system of the present application is divided into two parts: constant parameter acquisition and dynamic environmental factor monitoring. The model parameter table constructed by the present application is shown in Table 1 below, and the model variable table is shown in Table 2 below:

[0029] Table 1 Model parameter table

[0030]

[0031] Table 2 Model variable table

[0032]

[0033] The core function module is used to simulate the exchange flux of black-smelly substances at the land pipeline, land-water interface, air-water interface and mud-water interface, and the material accumulation information in the land pipeline, water body and sediment based on the environmental monitoring data through the system dynamics model, and determine the pollutant simulation result. In an embodiment, the six core function modules (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) are analyzed, which specifically includes the following (1) to (6):

[0034] (1) 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 land pipeline material accumulation, to determine the dynamic change information of black-smelly substances in the land pipeline. Specifically, in the generalization model, only the organic matter (COD) accumulation in the land pipeline is considered, and the model is shown in the following formula (1): ), 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):

[0035] (a) Accumulation of organic matter in land-based pipelines ( ):

[0036]

[0037] (b) Sulfide accumulation in land-based pipelines ):

[0038]

[0039] (c) Accumulation of ammonium nitrogen in land-based pipelines ( ):

[0040]

[0041] 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)).

[0042] 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.

[0043] (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):

[0044] (a) Organic matter exchange at the land-water interface ):

[0045]

[0046] (b) Sulfide exchange at the land-water interface ):

[0047]

[0048] (c) Ammonium nitrogen exchange at the land-water interface ):

[0049]

[0050] 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 water body pollutant concentration (unit: mg / L) includes the water body organic matter concentration , sulfide concentration , and ammonium nitrogen concentration . The substance transport process is controlled by the land-water interface general mass transfer coefficient (unit: m / h), which mainly depends on the key environmental factor of rainfall intensity (unit: mm / h).

[0051] That is, the above formula group describes the exchange flux of the land-water interface dissolved pollutants, the driving force is the concentration difference between the land and the water body, the generalization model assumes that different components have the same mass transfer coefficient, and the mass transfer coefficient is only related to the rainfall intensity, and the effects of temperature and dissolved oxygen and dynamic hysteresis are ignored.

[0052] (3) The air-water interface module, wherein the air-water interface module is used for analyzing and processing the sulfide exchange information and the ammonium nitrogen exchange information of the air-water interface according to the pollutant concentration difference between the gas and the water body and combining the Henry constant to balance the volatile state, to determine the exchange flux of the air-water interface pollutants. Specifically, in the generalization model, the air-water interface substance exchange flux mainly considers the exchange of two key gaseous pollutants, sulfide ( ) and ammonium nitrogen ( ), and assumes that the mass transfer coefficients of the two are the same. The generalization air-water interface substance exchange flux equation group includes the following (a) to (b):

[0053] (a) Sulfide exchange ( ) of the air-water interface:

[0054]

[0055] (b) Ammonium nitrogen exchange ( ) of the air-water interface:

[0056]

[0057] Wherein, in the air-water interface substance exchange process, the fluxes of two components, sulfide and ammonium nitrogen and (milligrams per square meter per hour, mg / m²·h) are mainly involved. These fluxes are affected by the concentrations of the corresponding pollutants in the water body and (unit: mg / L) and the pollutant concentrations in the atmosphere and mg / m³) and where the sulphide and ammonium in the atmosphere are mainly present as H2S and NH3, the mass transport process is governed by the general mass transfer coefficient (m / h) which is mainly dependent on the wind speed (m / s), and the Henry's constants of sulphide and ammonium nitrogen and (dimensionless) which vary with temperature (°C) and are key parameters describing the partitioning equilibrium of these substances between the gas and liquid phase.

[0058] That is, the above set of equations describes the gas exchange fluxes of sulphide and ammonium at the air-water interface, the driving force being the concentration difference between the gas and liquid phase, and the influence of the Henry's constant on the volatilization equilibrium is considered. The general model assumes that sulphide and ammonium have the same mass transfer coefficient which is only dependent on the wind speed. Minor processes such as vertical diffusion are neglected. The component specificity and temperature dependence of the Henry's constant are retained.

[0059] (4) The sediment-water interface module, wherein the sediment-water interface module is configured to analyze and process the exchange information of organic matter, the exchange information of sulphide and the exchange information of ammonium at the air-water interface according to the concentration difference of pollutants between the sediment pore water and the water body and a preset partition coefficient, to determine the exchange flux of the dissolved pollutants at the sediment-water interface, and specifically, in the general model, the exchange flux of the substances at the sediment-water interface only considers three components of organic matter ( ), sulphide ( ) and ammonium ( ), and assumes that different components have the same mass transfer coefficient, and diffusion is neglected. The general exchange flux equation of the substances at the sediment-water interface includes the following (a) to (c):

[0060] (a) Exchange of organic matter at the sediment-water interface ( ):

[0061]

[0062] (b) Exchange of sulphide at the sediment-water interface ( ):

[0063]

[0064] (c) Exchange of ammonium at the sediment-water interface ( ):

[0065]

[0066] In the exchange process of the substances at the sediment-water interface, the flux mainly includes the flux of organic matter , the flux of sulphide 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.

[0067] 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.

[0068] (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):

[0069] (a) Accumulation of organic matter in water bodies ):

[0070]

[0071] (b) Sulfide accumulation in the water body

[0072]

[0073] (c) Ammonium accumulation in the water body

[0074]

[0075] wherein the component concentrations during the water body material accumulation process mainly include water body organic matter concentration , water body sulfide concentration and water body ammonium concentration (unit: mg / L). The interface fluxes include land-water interface fluxes , and from the general formula in step (2) above, , and from the general formula in step (3) above (wherein only sulfide and ammonium fluxes are possible in the general formula in step (3) above, and the organic matter flux can be 0), and sediment-water interface fluxes , and from the general formula in step (3) above (unit: mg / m²·h). These interface fluxes act on land-water interface area , air-water interface area and sediment-water interface area (unit: m²) respectively.

[0076] In terms of pipe input, it includes pipe pollutant concentrations of each component , and (unit: mg / L) from the general formula in step (1) above, and pipe drainage flow (unit: m³ / h). The key reaction rate coefficients include temperature-dependent organic matter anaerobic fermentation rate coefficient and dissolved oxygen-dependent sulfide oxidation rate coefficient (unit: 1 / h). The maximum microbial degradation rate includes temperature-dependent maximum degradation rate of water body aerobic heterotrophic bacteria , maximum degradation rate of water body sulfate reducing bacteria and maximum degradation rate of water body sulfide oxidizing bacteria (unit: mg / L·h).​​

[0077] 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).

[0078] 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.

[0079] (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)

[0080] (a) Accumulation of organic matter in sediments ):

[0081]

[0082] (b) Accumulation of sulfides in sediments

[0083]

[0084] (c) ammonium accumulation in sediments

[0085]

[0086] where the component concentrations include the organic matter concentration in sediments (C0M), the sulfide concentration in sediments (Cs), and the ammonium concentration in sediments (C ), all in units of milligrams per liter (mg / L). is the interfacial flux from the general formulation in step (4) above (in units of mg / m2·h). is the active layer thickness of the sediments (in units of m) used to convert the interfacial flux to the rate of concentration change in the sediments. The key reaction rate coefficients include the temperature-dependent (T) rate coefficient for anaerobic fermentation of organic matter in sediments (k and the dissolved oxygen (DO)-dependent (k ) rate coefficient for oxidation of sulfide in sediments, both in units of per hour (1 / h). The maximum degradation rates of microorganisms include the maximum degradation rates of aerobic heterotrophic bacteria in sediments (r , sulfate-reducing bacteria in sediments (r , and sulfide-oxidizing bacteria in sediments (r , all of which are temperature-dependent and in units of milligrams per liter per hour (mg / L·h). The half-saturation constants include the half-saturation constants of aerobic heterotrophic bacteria in sediments (K , sulfate-reducing bacteria in sediments (K , and sulfide-oxidizing bacteria in sediments (K , all in units of milligrams per liter (mg / L). The concentrations of microorganisms include the concentrations of aerobic heterotrophic bacteria in sediments (C , sulfate-reducing bacteria in sediments (C , and sulfide-oxidizing bacteria in sediments (C , all of which are assumed to be constant and in units of milligrams per liter (mg / L). The yield coefficients include the yield coefficient for sulfide production from organic matter degradation by sulfate-reducing bacteria (Y ) and the yield coefficient for ammonium production from organic matter ammonification (Y ). The environmental factors include temperature (T in units of degrees Celsius °C) and dissolved oxygen (DO in units of milligrams per liter mg / L), which are the same as those in the water body.

[0087] ​​​​​​That is, the above formula set describes the dynamic change of key black and odorous substances in the sediment, which is jointly affected by the exchange of substances at the sediment-water interface and the biochemical reactions inside the sediment. The simplified model assumes that the concentration of microorganisms in the sediment is constant and simplifies the dependence of reaction rate on environmental factors. Minor processes such as sediment diffusion are ignored. The generalized formula from step (4) above and the generalized formula from step (6) above are coupled through the sediment-water interface flux term.

[0088] The model verification module is configured to divide the environmental monitoring data into a calibration set and a verification set, and evaluate the performance of the model based on the calibration set and the verification set after parameter calibration through the model evaluation unit. The model verification module includes a data set division unit configured to divide the data into a calibration set and a verification set; a parameter optimization unit configured to optimize the model parameters; and a model evaluation unit configured to evaluate the performance of the model.

[0089] The scenario analysis module is configured to, when the performance of the model is evaluated, perform full-coupling simulation on the risk of blackening and odor returning of the water body corresponding to each preset urban scenario according to the simulation results of the pollutants to determine the target risk assessment results. When evaluating the risk evolution law of the blackening and odor returning of the urban water body under different conditions, the following (1) to (3) are mainly included:

[0090] (1) Rainfall scenario analysis: The system systematically studies the influence mechanism of the rainfall process on the water quality of the water body, focuses on analyzing the quantitative effect of rainfall intensity in the range of 0-50 mm / h on the pollutant input at the land-water interface, and comparatively studies the difference in water quality under continuous rainfall and intermittent rainfall conditions. By establishing a quantitative evaluation system of the initial rainwater scouring effect, combining the accumulation and scouring dynamics characteristics of pollutants in the rainfall-runoff process, the full-process simulation and analysis of water quality changes under rainfall conditions are realized.

[0091] (2) Engineering measure scenario analysis: The scenario analysis of the system on engineering measures mainly carries out in-depth research from two aspects of pipe network system reconstruction and sediment treatment. In terms of pipe network system reconstruction, the influence mechanism of engineering measures such as improving the water conveying capacity of the pipe network and dredging the sediment in the pipeline on the pollutant migration and transformation process is evaluated. 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 influence of various measures including ecological restoration on the exchange process of substances at the sediment-water interface is evaluated, so as to provide scientific decision basis for engineering practice.

[0092] (3) Environmental factor scenario analysis: The system's scenario analysis of environmental factors mainly focuses on two key aspects: temperature and hydrological conditions. In terms of temperature changes, the system focuses on the impact mechanisms 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. In terms of changes in hydrological conditions, the system in-depth analyzes the impact mechanisms of flow rate changes and water level fluctuations on interface material exchange, thereby achieving a systematic evaluation of the impact of hydrological factors.

[0093] Based on Figure 1 Figure 1 is a structural schematic diagram of a city water body blackening and malodorous risk assessment system based on multi-interface coupling according to the present application, and Figure 2 Figure 2 is a specific structural schematic diagram of a city water body blackening and malodorous risk assessment system based on multi-interface coupling according to the present application. The embodiments of the present application introduce in detail the city water body blackening and malodorous risk assessment method based on multi-interface coupling, referring to Figure 3 Figure 3 is a flow schematic diagram of a city water body blackening and malodorous risk assessment method based on multi-interface coupling according to the present application. The method mainly includes the following steps S302 to S306:

[0094] Step S302, environmental monitoring data is acquired, wherein the environmental monitoring data includes constant parameters and dynamic environmental factors.

[0095] Step S304, the constant parameters and dynamic environmental factors are analyzed and processed by using the land pipeline module, the land-water interface module, the air-water interface module, the mud-water interface module, the substance accumulation module in the water body, and the substance accumulation module in the sediment, respectively, to determine the pollutant simulation results, wherein the pollutant simulation results include the dynamic change information of black and odorous substances in the land pipeline, the exchange flux of dissolved pollutants at the land-water interface, the exchange flux of pollutants at the air-water interface, the exchange flux of dissolved pollutants at the mud-water interface, the dynamic change information of black and odorous substances in the water body, and the dynamic change information of black and odorous substances in the sediment. In an embodiment, the full coupling simulation of the land pipeline, the land-water interface, the air-water interface, and the mud-water interface based on the system integration effect can overcome the limitations of traditional single interface models. In addition, by establishing a unified mathematical framework, the system systematically describes the material transport and interaction between interfaces, which can make the prediction results more consistent with the actual process of black and odorous substance migration and transformation in the water body.

[0096] Further, by using the system dynamics method to construct the model, the dynamic changes of the concentration of black and odorous substances in the water body can be simulated. By establishing the material transport equation of each interface, the water body substance accumulation equation, and the sediment substance accumulation equation, the system can accurately reflect the influence of external condition changes (such as rainfall, pollution discharge, etc.) on water quality. Especially in the prediction of sudden pollution events or the evaluation of the effect of treatment measures, the system can show excellent dynamic response performance.

[0097] Step S306, according to the pollutant simulation results, the water body black and smelly risk corresponding to each preset city scene is simulated in full coupling, and the target risk assessment result is determined. In an embodiment, the scene analysis function is an important technology to support decision-making. Through the integration of the scene analysis module, the control effect of water body black and smelly under different management strategies can be simulated. By adjusting the model parameters, the effect of various treatment measures (such as source control, sediment dredging, and oxygenation) can be predicted, thereby providing a scientific basis for management decision-making.

[0098] Further, for the above step S304, a nonlinear mathematical model system considering the interface coupling effect is constructed, which is specifically referred to as (1) to (6) as follows:

[0099] (1) Accumulation of substances in the land pipeline:

[0100]

[0101] wherein, represents the concentration vector of various pollutants in the pipeline (mg / L), is time (h), is the input rate vector of various pollutants (mg / L·h), is the output rate vector of various pollutants (mg / L·h), is the temperature and dissolved oxygen dependent degradation coefficient matrix, including: organic matter anaerobic fermentation rate coefficient and sulfide oxidation rate coefficient ( ), is the maximum degradation rate of the i-th microorganism, including: aerobic heterotrophic bacteria , sulfate reducing bacteria and sulfide oxidizing bacteria ( ), is the corresponding half-saturation constant (mg / L), is the concentration of various microorganisms, including: , and (mg / L).

[0102] (2) Material exchange at the land-water interface:

[0103]

[0104] wherein, represents the flux vector of various pollutants at the land-water interface:

[0105] (mg / m²·h)

[0106] where, is the mass transfer coefficient (m / h), is the rainfall intensity (mm / h), denotes the concentration vector of pollutants in the land (mg / L), denotes the concentration vector of pollutants in the water (mg / L). denotes the concentration vector of pollutants in the water (mg / L). denotes the concentration vector of pollutants in the water (mg / L).

[0107] (3) Mass exchange at the air-water interface:

[0108]

[0109] where, denotes the flux vector of pollutants at the air-water interface (mg / m2·h), is the mass transfer coefficient (m / h), is the wind speed (m / s), denotes the Henry constant vector of components (dimensionless), is the temperature (°C), denotes the concentration vector of pollutants in the water (mg / L), denotes the concentration vector of pollutants in the air (mg / m3). denotes the concentration vector of pollutants in the water (mg / L). denotes the concentration vector of pollutants in the air (mg / m3). denotes the concentration vector of pollutants in the water (mg / L). denotes the concentration vector of pollutants in the air (mg / m3).

[0110] (4) Mass exchange at the sediment-water interface:

[0111]

[0112] where, denotes the flux vector of pollutants at the sediment-water interface (mg / m2·h), is the mass transfer coefficient (m / h), mainly dependent on the dissolved oxygen (DO) and oxidation-reduction potential (ORP), denotes the concentration vector of pollutants in the pore water of sediment (mg / L), denotes the partition coefficient vector of components (L / kg), denotes the concentration vector of pollutants in the water (mg / L). denotes the concentration vector of pollutants in the water (mg / L). denotes the concentration vector of pollutants in the water (mg / L). denotes the concentration vector of pollutants in the water (mg / L). denotes the concentration vector of pollutants in the water (mg / L). denotes the concentration vector of pollutants in the water (mg / L).

[0113] (5) Accumulation of pollutants in the water:

[0114]

[0115] where, Ci represents a concentration vector of various pollutants in the water body (mg / L), V represents a volume of the water body (m³), , , F represents a flux vector of various pollutants at the interface between the land water, the air water and the mud water (mg / m²·h), , , A represents an area of the interface between the land water, the air water and the mud water (m²), Q represents a flow rate of the pipeline (m³ / h), Ci represents a concentration vector of various pollutants in the pipeline (mg / L), K represents a temperature-dependent degradation coefficient matrix, μi represents a maximum degradation rate of the i-th type of microorganism (including aerobic heterotrophic bacteria, sulfate-reducing bacteria and sulfide-oxidizing bacteria, ), Ks represents a corresponding half-saturation constant (mg / L), Ci represents a concentration of various microorganisms in the water body (mg / L).

[0116] (6) Accumulation of substances in the sediment:

[0117] In order to simplify the model, the accumulation of substances in the sediment only considers the accumulation and transformation of various key pollutant components, the concentration of microorganisms is assumed to be constant, and the dependence of the reaction rate on the environmental factors is simplified. The following is a general differential equation for the simplified accumulation of substances in the sediment:

[0118]

[0119] wherein, Ci represents a concentration vector of various pollutants in the sediment (mg / L), Fi represents a flux vector of various pollutants at the interface between the mud water and the water (mg / m²·h), H represents a thickness of an active layer of the sediment (m), μ represents a biochemical reaction rate vector in the sediment.

[0120] The embodiment of the present application also provides an implementation of model calibration and verification. The model verification module comprises a data set division unit, a parameter optimization unit and a model evaluation unit. Specifically, refer to (1) to (3) as follows:

[0121] (1) The data set division unit: all available data are divided into a calibration set and a verification set according to a ratio of 7:3. The calibration set is mainly used for optimizing and adjusting the model parameters and performing sensitivity analysis, and the verification set is used for independently evaluating the prediction ability and stability of the model to ensure the reliability and practicability of the model.

[0122] (2) Parameter optimization unit: first, systematically collect historical monitoring data 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.), pollutant concentration data of each interface (such as 、 、 、 , etc.) and hydrological parameters (such as flow, water level, etc.), on this basis, parameter calibration is carried out to ensure the scientificity and reliability of model parameters.

[0123] (3) Model evaluation unit: use independent validation data set to evaluate model performance, use multi-level statistical indicators for evaluation:

[0124] Root mean square error (RMSE):

[0125]

[0126] Coefficient of determination (R²):

[0127]

[0128] Nash-Sutcliffe efficiency coefficient (NSE):

[0129]

[0130] Relative error (RE):

[0131]

[0132] Wherein, is the observed value, is the predicted value, and are the average values of the observed value and the predicted value, respectively.

[0133] In summary, the present application can unify the material transport processes of land pipeline, land-water interface, air-water interface and mud-water interface into one mathematical framework through multi-interface coupling modeling technology, and realize the quantitative coupling of each interface flux through the accumulation equation of the central processing module, at the same time, a complete interface mass transfer equation set is established, which ensures that the model has clear physical meaning; through the nonlinear feedback mechanism, the nonlinear influence of environmental factors is considered, and the kinetic characteristics of biodegradation are described, the dynamic change of interface flux is simulated to reflect the adaptive characteristics of the system; finally, through the scenario analysis function, an evaluation method of different management strategies is established, the influence evaluation module of rainfall, hydrology, temperature, engineering measures is developed, and the multi-scenario comparison analysis function is designed, through these technical means, scientific basis is provided for management decision.

[0134] The embodiment of the present application provides a server, and specifically, the server comprises a processor and a storage device; the storage device stores a computer program, and the computer program performs the method of any one of the above embodiments when the computer program is run by the processor.

[0135] Figure 4 A structural diagram of a server provided by the embodiment of the present application is shown in the figure, the server 100 comprises 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 for executing an executable module stored in the memory 41, for example, a computer program.

[0136] The memory 41 can contain a high-speed random access memory (RAM), and can also include a non-volatile memory, for example, at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 43 (which can be wired or wireless), and the Internet, a wide area network, a local area network, a metropolitan area network and the like can be used.

[0137] The bus 42 can be an ISA bus, a PCI bus or an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 4 Only one bidirectional arrow is used in the figure, but it does not mean that there is only one bus or only one type of bus.

[0138] The memory 41 is used for storing a program, and the processor 40 executes the program after receiving an execution instruction; the method executed by the device defined by the flow process disclosed in any one of the above embodiments of the present application can be applied to the processor 40 or realized by the processor 40.

[0139] The processor 40 can be an integrated circuit chip with signal processing capability. In implementation, the steps of the above method can be completed by integrated logic circuits or instructions in the form of software in the processor 40. The processor 40 described above can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. The disclosed methods, steps and logic block diagrams in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor for execution. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium in the art. The storage medium is located in the memory 41, and the processor 40 reads the information in the memory 41, and combines the hardware to complete the steps of the above method.

[0140] The computer program product of the readable storage medium provided by the embodiments of the present application includes a computer readable storage medium storing program codes, and the program codes include instructions for executing the method described in the foregoing method embodiments. For specific implementation, please refer to the foregoing method embodiments, which will not be described here.

[0141] When the function is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the part of the technical solutions that essentially contribute to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for making a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in the embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc. Various media that can store program codes.

[0142] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present application, and are used to illustrate the technical solutions of the present application, but are not limitations thereof. The protection scope of the present application is not limited thereto. Although the present application 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 make modifications or easily think of changes to the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some of the technical features within the technical range disclosed by the present application. The modifications, changes or replacements do not cause the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A multi-interface coupling-based urban water body blackening and malodorous risk assessment system, characterized in that, The system comprises a parameter acquisition module, a core function module, a model verification module and a scenario analysis module, wherein The parameter acquisition module is configured to acquire environmental monitoring data collected by sensors, wherein the environmental monitoring data comprises constant parameters and dynamic environmental factors, the constant parameters comprise half-saturation constants of various microorganisms, distribution coefficient vectors of various components, sulfide production coefficients of sulfate-reducing bacteria, ammonification ammonium nitrogen production coefficients of organic matter, volumes of water bodies, areas of land-water interfaces, areas of air-water interfaces, areas of mud-water interfaces and thicknesses of active layers of sediments, and the dynamic environmental factors comprise concentration vectors of various pollutants in pipelines, concentration vectors of various pollutants in land areas, concentration vectors of various pollutants in water bodies, concentration vectors of various pollutants in sediments, concentration vectors of various pollutants in the atmosphere, flux vectors of various pollutants at land-water interfaces, flux vectors of various pollutants at air-water interfaces, flux vectors of various pollutants at mud-water interfaces, temperatures, dissolved oxygen, oxidation-reduction potentials, rainfall intensities, wind speeds and pipeline drainage flow rates; The core function module is configured to simulate exchange fluxes of black and odorous substances at land-water interfaces, air-water interfaces and mud-water interfaces, and material accumulation information in land pipelines, water bodies and sediments based on the environmental monitoring data by a system dynamics model, and determine pollutant simulation results, wherein the black and odorous substances are determined by accumulation information of organic matter, sulfides and ammonium nitrogen in land pipelines; The model verification module is configured to divide the environmental monitoring data into a calibration set and a verification set, and evaluate model performance based on the calibration set and the verification set after parameter calibration by a model evaluation unit; The scenario analysis module is configured to perform full-coupling simulation on water body blackening and odorizing risks corresponding to each preset urban scenario according to the pollutant simulation results when the model performance evaluation passes, and determine target risk evaluation results.

2. The multi-interface coupling-based urban water body blackening and malodorous risk assessment system according to claim 1, wherein The core function module comprises a land pipeline module, wherein The land pipeline module is configured to analyze and process accumulation information of organic matter, sulfides and ammonium nitrogen in land pipelines based on an analysis model of land pipeline material accumulation, so as to determine dynamic change information of black and odorous substances in land pipelines.

3. The multi-interface coupling-based urban water body blackening and malodorous risk assessment system according to claim 1, characterized in that, The core function module comprises a land-water interface module, wherein The land-water interface module is configured to analyze and process exchange information of organic matter, sulfides and ammonium nitrogen at land-water interfaces based on concentration differences of pollutants between land areas and water bodies, so as to determine exchange fluxes of dissolved pollutants at land-water interfaces.

4. The multi-interface coupling based urban water body blackening and malodorous risk assessment system according to claim 1, characterized in that, The core function module comprises an air-water interface module, wherein The air-water interface module is configured to analyze and process exchange information of sulfides and ammonium nitrogen at air-water interfaces based on concentration differences of pollutants between gases and water bodies and balance of volatile states combined with Henry's constant, so as to determine exchange fluxes of pollutants at air-water interfaces.

5. The multi-interface coupling based urban water body blackening and malodorous risk assessment system according to claim 1, characterized in that, The core function module comprises a mud-water interface module, wherein The mud-water interface module is configured to analyze and process exchange information of sulfides and ammonium nitrogen at mud-water interfaces based on concentration differences of pollutants between mud and water, so as to determine exchange fluxes of pollutants at mud-water interfaces. The mud-water interface module is used for analyzing and processing organic exchange information, sulfide exchange information and ammonium nitrogen exchange information of the air-water interface according to a difference in pollutant concentration between sediment pore water and the water body, and a preset distribution coefficient, so as to determine exchange flux of the dissolved pollutant of the mud-water interface.

6. The multi-interface coupling based urban water body blackening and malodorous risk assessment system according to claim 1, characterized in that, The core function module comprises a substance accumulation module in the water body; wherein, The substance accumulation module in the water body is used for analyzing and processing organic accumulation information, sulfide accumulation information and ammonium nitrogen accumulation information in the water body according to an analysis model of water body substance accumulation, so as to determine dynamic change information of the black and odorous substance in the water body.

7. The multi-interface coupling based urban water body blackening and malodorous risk assessment system according to claim 1, characterized in that, The core function module comprises a substance accumulation module in the sediment; wherein, The substance accumulation module in the sediment is used for analyzing and processing organic accumulation information, sulfide accumulation information and ammonium nitrogen accumulation information in the sediment according to an analysis model of sediment substance accumulation, so as to determine dynamic change information of the black and odorous substance in the sediment.

8. A method for risk assessment of blackening and malodorous of urban water body based on multi-interface coupling, characterized in that, The method is applied to a city water body blackening and odorizing risk assessment system based on multi-interface coupling, and the method comprises: obtaining environmental monitoring data, wherein the environmental monitoring data comprises constant parameters and dynamic environmental factors, the constant parameters comprise half-saturation constants of various microorganisms, distribution coefficient vectors of various components, sulfide production coefficients of sulfate-reducing bacteria, ammonium nitrogen production coefficients of organic matter, a volume of the water body, an area of the land-water interface, an area of the air-water interface, an area of the mud-water interface, and a thickness of the active layer of the sediment, and the dynamic environmental factors comprise concentration vectors of various pollutants in the pipeline, concentration vectors of various pollutants in the land, concentration vectors of various pollutants in the water body, concentration vectors of various pollutants in the sediment, concentration vectors of various pollutants in the atmosphere, flux vectors of various pollutants of the land-water interface, flux vectors of various pollutants of the air-water interface, flux vectors of various pollutants of the mud-water interface, temperature, dissolved oxygen, oxidation-reduction potential, rainfall intensity, wind speed, and pipeline drainage flow rate; the constant parameters and the dynamic environmental factors are analyzed and processed by using a land pipeline module, a land-water interface module, an air-water interface module, a mud-water interface module, a substance accumulation module in the water body, and a substance accumulation module in the sediment, respectively, so as to determine pollutant simulation results, wherein the pollutant simulation results comprise dynamic change information of the black and odorous substance in the land pipeline, exchange flux of the dissolved pollutant of the land-water interface, exchange flux of the pollutant of the air-water interface, exchange flux of the dissolved pollutant of the mud-water interface, dynamic change information of the black and odorous substance in the water body, and dynamic change information of the black and odorous substance in the sediment, and the black and odorous substance is determined by accumulation information of organic matter, sulfide and ammonium nitrogen in the land pipeline; the water body blackening and odorizing risk corresponding to each preset city scenario is simulated in full coupling according to the pollutant simulation results, so as to determine a target risk assessment result.

9. A server, characterized by The device comprises a processor and a memory, the memory stores computer executable instructions capable of being executed by the processor, and the processor executes the computer executable instructions to implement the method in 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 the processor, cause the processor to implement the method of claim 8.

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