Bioretention purification method and device for port and wharf rainwater collection and treatment and readable storage medium

Abstract

The invention discloses a bioretention purification method and device for port and wharf rainwater collection and treatment and a readable storage medium. The method comprises the steps that firstly, port area storage yard drainage ditch rainwater primarily filtered through a grid is collected through a rainwater collection pipe, and then deep purification is conducted through a biological filter with a multi-layer structure including a vegetation layer, a water diversion layer and the like; and storing the filtered rainwater into a target water collecting tank. And then evaluating the water quality of the water collecting tank according to a preset time interval, and if the bioretention purification is passed, configuring a reclaimed water reuse task for the bioretention purification. According to the method, port and wharf rainwater purification and recycling are achieved, and the water resource utilization rate is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of port management, and more particularly, to a biological retention purification method, device and readable storage medium for rainwater collection and treatment in port terminals. Background Art

[0002] In the operation of port terminals, rainwater runoff carries pollutants, and direct discharge will cause water pollution. Traditional rainwater treatment methods have problems such as low efficiency and inability to specifically treat rainwater in different areas. Existing technologies are difficult to effectively collect and treat rainwater with different pollution degrees in different functional areas of ports, and do not fully consider rainwater reuse. The present invention aims to provide an efficient biological retention purification method for rainwater collection and treatment in port terminals, realizing classified collection, deep purification and reasonable reuse of rainwater, and solving the problems of rainwater pollution and water resource utilization in port areas. Summary of the Invention

[0003] The purpose of the present invention is to provide a biological retention purification method, device and readable storage medium for rainwater collection and treatment in port terminals.

[0004] In a first aspect, an embodiment of the present invention provides a biological retention purification method for rainwater collection and treatment in port terminals, including: Collecting rainwater from the drainage ditch of the port yard that has been preliminarily filtered by a grille through a rainwater collection pipe; Deeply purifying the rainwater through a biological filter tank, and storing the deeply purified rainwater in a target water collection tank through a water collection pipe; the biological filter tank includes a vegetation layer, a water distribution layer, a microbial filler layer, a supporting layer and a percolation layer; Evaluating the water quality of the target water collection tank at preset time intervals to obtain a water quality evaluation result; When the water quality evaluation result indicates that the biological retention purification is passed, configuring a reclaimed water reuse task for the target water collection tank.

[0005] In a possible implementation manner, the cross-section of the biological filter tank is arc-shaped; The vegetation layer is located on the side of the biological filter tank close to the ground, and the vegetation layer is composed of preset port plant species, and the vegetation layer is used to filter and intercept the substances not filtered by the grille carried in the runoff rainwater; The water distribution layer is located on the side of the vegetation layer away from the ground, and the water distribution layer is filled with quartz sand, and the water distribution layer is used to filter and control the uniform infiltration of rainwater; The microbial filler layer is located on the side of the water distribution layer away from the vegetation layer, and the microbial filler layer is composed of a combination of activated carbon particles inoculated with a composite microbial membrane, and the microbial filler layer inoculates corresponding functional microorganisms based on the characteristics of rain and sewage in different areas of the port; The supporting layer is located on the side of the microbial filler layer away from the water distribution layer. The supporting layer is filled with gravel and is used to support the vegetation layer, the water distribution layer, and the microbial filler layer. The percolation layer is located on the side of the supporting layer away from the microbial filler layer. The percolation layer is filled with zeolite and is used to filter and adsorb pollutants.

[0006] In a possible implementation manner, performing a water quality assessment on the target sump at preset time intervals to obtain a water quality assessment result, including: Performing a feature extraction operation on the water quality samples to be evaluated in the set of water quality samples to be evaluated at preset time intervals to obtain a set of water quality features. Among them, the set of water quality samples to be evaluated includes a plurality of water quality samples to be evaluated for different monitoring points indicating the target sump, and the set of water quality features includes a plurality of water quality features arranged in the order of preset monitoring points; Determining a target water quality feature and a target partition evaluation sub-vector corresponding to the target water quality feature from the set of water quality features according to the position information of the monitoring points characterized by the water quality samples to be evaluated in the set of water quality samples to be evaluated; Using the target water quality feature as a feature reference parameter and a feature weight parameter respectively, and using the target partition evaluation sub-vector as an evaluation condition parameter to perform water quality association mapping processing to obtain the sub-features of the partition water quality; Obtaining a comprehensive water quality feature according to the plurality of sub-features of the partition water quality. Among them, the evaluation vector includes a plurality of evaluation unit parameters, and the evaluation unit parameters are used to indicate the sump partition characteristics of the target sump; Determining the type of pollution of the comprehensive water quality feature to obtain the probability of the basic pollution category; Determining the pollution partition of the comprehensive water quality feature to obtain the basic pollution partition identifier; Obtaining the basic water quality assessment result according to the probability of the basic pollution category and the basic pollution partition identifier; Removing the evaluation unit parameters in the evaluation vector according to the basic water quality assessment result to obtain an optimized evaluation vector; Obtaining a water quality assessment result according to the optimized evaluation vector and the set of water quality features.

[0007] In a possible implementation manner, the basic water quality assessment result includes a plurality of probabilities of the basic pollution category and a plurality of basic pollution partition identifiers having a mapping relationship with the plurality of probabilities of the basic pollution category. The plurality of basic pollution partition identifiers have a mapping relationship with the plurality of evaluation unit parameters in the evaluation vector; Removing the evaluation unit parameters in the evaluation vector according to the basic water quality evaluation result to obtain an optimized evaluation vector, including: For each of the basic pollution zone identifiers, determining the evaluation unit parameters to be removed corresponding to the basic pollution zone identifier from the evaluation vector; Determining the parameter removal determination of the evaluation unit parameters to be removed according to the basic pollution category probability and the pollution determination threshold corresponding to the basic pollution zone identifier; Removing the evaluation unit parameters in the evaluation vector according to multiple parameter removal determinations to obtain the optimized evaluation vector.

[0008] In a possible implementation manner, the basic water quality evaluation result includes multiple basic pollution category probabilities and multiple basic pollution zone identifiers having a mapping relationship with the multiple basic pollution zone identifiers, and the multiple basic pollution zone identifiers have a mapping relationship with multiple evaluation unit parameters in the evaluation vector; Removing the evaluation unit parameters in the evaluation vector according to the basic water quality evaluation result to obtain an optimized evaluation vector, including: Determining a sub-vector of the evaluation zones to be removed corresponding to the preset monitoring area in the target sump from the evaluation vector; Determining a specified number of target basic pollution category probabilities corresponding to the preset monitoring area from the multiple basic pollution category probabilities according to the multiple basic pollution zone identifiers; Removing the evaluation unit parameters in the sub-vector of the evaluation zones to be removed according to the basic pollution zone identifiers of the specified number of target basic pollution category probabilities respectively to obtain the optimized sub-vector of the evaluation zones; Obtaining the optimized evaluation vector according to multiple optimized sub-vectors of the evaluation zones.

[0009] In a possible implementation manner, obtaining the water quality evaluation result according to the optimized evaluation vector and the water quality feature set, including: Obtaining a target comprehensive water quality feature according to the optimized evaluation vector and the water quality feature set; Performing pollution type determination on the target comprehensive water quality feature to obtain a pollution category probability; Performing pollution zone determination on the target comprehensive water quality feature to obtain a pollution zone identifier; Obtaining the water quality evaluation result according to the pollution category probability and the pollution zone identifier.

[0010] In a possible implementation manner, obtaining the target comprehensive water quality feature according to the optimized evaluation vector and the water quality feature set includes: Performing pollution feature interaction processing on the optimized evaluation vector to obtain a target evaluation vector; Performing water quality correlation analysis on the target evaluation vector and the water quality feature set to obtain the target comprehensive water quality feature; Obtaining the target comprehensive water quality feature according to the optimized evaluation vector and the water quality feature set further includes: When it is determined that the current cycle is less than the preset number of cycles, performing pollution feature interaction processing on the target evaluation vector of the previous cycle to obtain the target evaluation vector of the current cycle; Performing water quality correlation analysis on the target evaluation vector of the current cycle and the comprehensive water quality feature of the previous cycle to obtain the comprehensive water quality feature of the current cycle; When it is determined that the current cycle is equal to the preset number of cycles, determining the target comprehensive water quality feature according to the comprehensive water quality feature of the current cycle.

[0011] In a possible implementation manner, it further includes: Performing pollution feature interaction processing on the basic evaluation vector to obtain the evaluation vector, where the basic evaluation vector includes multiple dynamically adjustable evaluation unit parameters, and the dynamically adjustable evaluation unit parameters are trained through a historical water quality sample set and pollution level annotations corresponding to the historical water quality sample set.

[0012] In a second aspect, an embodiment of the present invention provides a bioretention purification device for rainwater collection and treatment at a port terminal, including: A purification module for collecting rainwater from the drainage ditch of the port yard that has been preliminarily filtered by a grille through a rainwater collection pipe; deeply purifying the rainwater through a biological filter pool, and storing the deeply purified rainwater in a target water collection pool through a water collection pipe; the biological filter pool includes a vegetation layer, a water distribution layer, a microbial filler layer, a support layer, and a percolation layer; An evaluation module for performing water quality evaluation on the target water collection pool at preset time intervals to obtain a water quality evaluation result; and configuring a reclaimed water reuse task for the target water collection pool when the water quality evaluation result indicates that the bioretention purification has passed.

[0013] In a third aspect, an embodiment of the present invention provides a readable storage medium, the readable storage medium includes a computer program, and when the computer program runs, it controls the computer device where the readable storage medium is located to execute the method described in the first aspect.

[0014] Compared with the prior art, the beneficial effects provided by the present invention include: adopting a bioretention purification method, device and readable storage medium for rainwater collection and treatment in a port terminal. The rainwater in the drainage ditch of the port yard after primary filtration through a grille is collected by a rainwater collection pipe, and then deeply purified by a bioretention filter with multiple layers such as a vegetation layer and a water diversion layer, and the filtered rainwater is stored in a target collection pool. Then, the water quality of the collection pool is evaluated at preset time intervals. If the bioretention purification passes, a task of reusing reclaimed water is configured for it. This method realizes the purification and reuse of rainwater in the port terminal and improves the utilization rate of water resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a schematic flowchart of the steps of the bioretention purification method for rainwater collection and treatment in a port terminal provided by an embodiment of the present invention; Figure 2 It is a schematic framework diagram of the bioretention purification system for rainwater collection and treatment in a port terminal provided by an embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of the bioretention purification device for rainwater collection and treatment in a port terminal provided by an embodiment of the present invention; Figure 4 It is a schematic block diagram of the structure of the computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and illustrated in the drawings here can be arranged and designed in various different configurations.

[0018] The following will describe the specific embodiments of the present invention in detail with reference to the drawings.

[0019] To solve the technical problems in the foregoing background art, Figure 1 It is a schematic flowchart of a bioretention purification method for rainwater collection and treatment in a port terminal provided by an embodiment of the present disclosure. The bioretention purification method for rainwater collection and treatment in a port terminal will be introduced in detail below.

[0020] Step S201: Collect the rainwater from the drainage ditches in the port yard that has been preliminarily filtered by the grille through the rainwater collection pipe. Step S202: Deeply purify the rainwater through the biological filter tank, and store the deeply purified rainwater in the target water collection tank through the water collection pipe; the biological filter tank includes a vegetation layer, a water distribution layer, a microbial filler layer, a supporting layer, and a percolation layer. Step S203: Conduct a water quality assessment on the target water collection tank at preset time intervals to obtain a water quality assessment result. Step S204: When the water quality assessment result indicates that the bioretention purification has passed, configure a reclaimed water reuse task for the target water collection tank.

[0021] In an embodiment of the present invention, by way of example, the server first conducts a detailed zoning of the port area, divides the port area into different areas such as a living area, a stacking area, a loading and unloading area, and a transfer area according to functions, and the stacking area is further subdivided into a container stacking area, a general cargo stacking area, a dry bulk cargo stacking area, etc. according to the type of goods. For the rain and sewage generated in different zones, a classified collection method is adopted. For example, the rain and sewage generated in the living area are relatively clean, and the main pollutants are impurities in domestic sewage. The server controls the rainwater collection facilities around the living area to guide the rain and sewage in this area to specific collection pipes, and these pipes are independent of the collection pipes in other areas to ensure that the rain and sewage in the living area will not be mixed with the rain and sewage in other areas.

[0022] For the stacking area, the pollution degree and types of pollutants in the rain and sewage of different types of stacking areas vary greatly. Taking the dry bulk cargo stacking area as an example, due to the storage of a large amount of goods such as ore and coal, when it rains, the rain and sewage carry a large amount of dust, scattered objects, and possible heavy metal pollutants. The server controls the pre-set drainage ditches around the stacking area to only collect the rain and sewage in this area, and transports it to the grille through an independent pipe for preliminary filtration.

[0023] The rain and sewage in the loading and unloading area may contain pollutants such as oil stains and mechanical wear debris generated during the loading and unloading process. The server collects the rain and sewage in the loading and unloading area through a dedicated rain and sewage collection device in the loading and unloading area, and imports it into a dedicated collection pipe for transportation to the subsequent treatment process.

[0024] The characteristics of the rain and sewage in the transfer area are also different. The server also adopts a classified collection method according to the characteristics of the transferred goods, and introduces the rain and sewage with different characteristics into the corresponding collection pipes respectively. By zoning the port area in this way and classifying the collection of rain and sewage according to the zones, it is possible to more specifically conduct subsequent treatment on rain and sewage with different pollution degrees and types, improving the efficiency and purification effect of rainwater collection and treatment.

[0025] Please refer to Figure 2 ,Figure 2 This is a schematic diagram of the framework of the bioretention purification system for rainwater collection and treatment in port terminals. After the server detects the water flow signal, the grid device is activated. The grid intercepts larger suspended solids and floating objects in the rainwater, such as coal blocks, ore particles, sundries, etc., to prevent them from entering the subsequent treatment process.

[0026] The rainwater preliminarily filtered by the grid flows along the established channel into the rainwater collection pipe. The server precisely controls the connection between the rainwater collection pipe and the yard to ensure that the filtered rainwater smoothly enters the collection pipe. These rainwater collection pipes are responsible for transporting the rainwater preliminarily filtered by the grid from the drainage ditches of each yard to the biological filter tank.

[0027] For example, after a medium rain in a large coal dry bulk yard area, the water flow in the drainage ditch is rapid, and the rainwater mixed with coal powder and small coal particles quickly converges. The grid starts to intercept larger coal particles, and the fine coal powder and rainwater enter the rainwater collection pipe. The server monitors the rainwater flow and impurity conditions in real time to ensure the normal operation of the collection pipe and prevent blockage.

[0028] Structure and function of the biological filter tank: The rainwater transported by the rainwater collection pipe flows into the biological filter tank. The biological filter tank is transformed based on the original port drainage channel or the vegetation landscape road. Its overall cross-section is arc-shaped, which can reduce the scouring of rainwater runoff. Its top width is designed according to the port road or the original landscape size, the bottom width is controlled at 0.5 - 1.5 m, and the slope gradient is determined in combination with the port soil properties and the length of the original drainage channel, generally not exceeding 1:3.

[0029] Purification process of the vegetation layer: The top layer of the biological filter tank is the vegetation layer. The server selects suitable vegetation for growth according to the port type (inland river or seaport). Taking the seaport area as an example, salt-tolerant herbaceous plants may be selected for the vegetation layer. When the rainwater flows into the biological filter tank, it first contacts the vegetation layer. The vegetation stems and leaves filter and intercept fine substances such as coal and ore dust in the runoff rainwater. For example, in the biological filter tank corresponding to the coal yard area, the plant roots in the vegetation layer adsorb coal powder, reducing the coal powder content in the rainwater. At the same time, the rainwater flow rate is slowed down, which is conducive to the rainwater infiltrating into the underlying soil layer.

[0030] Filtration and uniform infiltration of the water distribution layer: The rainwater passes through the vegetation layer and reaches the water distribution layer. The water distribution layer is located below the vegetation layer and is filled with quartz sand with a particle size of 2.0 - 5.0 mm, and the thickness is about 100 - 200 mm. The quartz sand further filters the remaining fine impurities in the rainwater and at the same time realizes the uniform infiltration of the rainwater, ensuring that the rainwater is evenly distributed to the underlying microbial packing layer below and guaranteeing the consistency of the purification effect of the biological filter tank.

[0031] Deep purification of the microbial packing layer: After passing through the water separation layer, the rainwater enters the microbial packing layer. This layer is composed of activated carbon particles inoculated with composite microbial membranes, with a thickness of about 20 - 50 mm. The server inoculates the composite microbial membranes with corresponding functional microorganisms or the activated sludge from the original sewage treatment plant according to the characteristics of rainwater and sewage in different zones of the port area. For example, in the dry bulk cargo area, denitrifying bacteria, polyphosphate-accumulating bacteria, etc. are inoculated for pollutants such as high-concentration total nitrogen, total phosphorus, organic matter, and heavy metals in rainwater and sewage. These microorganisms decompose and transform the pollutants in the rainwater on the surface of the activated carbon particles. For example, denitrifying bacteria convert nitrates into nitrogen gas to reduce the total nitrogen content, and polyphosphate-accumulating bacteria absorb phosphorus elements to remove phosphorus, significantly reducing the pollutant concentration in the rainwater.

[0032] Support function of the supporting layer: Below the microbial packing layer is the supporting layer, filled with 50 - 100 mm gravel, with a thickness of about 100 - 500 mm. The supporting layer supports the upper layers to prevent them from collapsing under the rainwater pressure. At the same time, the voids in the gravel provide channels for the flow of rainwater, ensuring the smooth downward penetration of rainwater.

[0033] Final purification and collection of the infiltration layer: Below the supporting layer is the infiltration layer, composed of 10 - 20 mm zeolite, with a layer thickness of 100 - 300 mm. The microporous structure of zeolite further filters and adsorbs the residual pollutants in the rainwater, improving the quality of rainwater. The server monitors the purification effect of the infiltration layer to ensure that the treated rainwater meets the standards. The treated rainwater is connected to the collecting pipe through the bottom of the infiltration layer. The collecting pipe is a PVC pipe with a trapezoidal cross-section and a sloping bottom. The upper section is porous for leaking the treated rainwater. These collecting pipes collect and transport the purified rainwater to the target collection pool for storage.

[0034] For example, in the biological filter corresponding to the ore dry bulk cargo yard area, the rainwater transported through the grille and rainwater collecting pipe passes through each layer for treatment in turn. The vegetation layer intercepts ore dust, the water separation layer equalizes the water flow and filters impurities, the microbial packing layer removes heavy metals and organic matter, the supporting layer stabilizes the structure, and the infiltration layer adsorbs the residual pollutants. Finally, the clear rainwater flows into the target collection pool through the collecting pipe, completing the deep purification and collection.

[0035] The target collection pool stores the rainwater deeply purified by the biological filter, and the server conducts a water quality assessment on it at preset time intervals.

[0036] The preset time interval is set according to the actual situation of the port terminal, such as every 24 hours or every 48 hours. When the preset time arrives, the server starts the water quality assessment program, controls the water quality detection equipment to sample the rainwater in the target collection pool, and the detection equipment collects representative water samples from different positions in the collection pool.

[0037] The water sample is transported to the water quality analysis unit. The server collaborates with the analysis unit, and the analysis unit detects indicators such as the acidity and alkalinity (pH value), chemical oxygen demand (COD), biochemical oxygen demand (BOD), total nitrogen, total phosphorus, and heavy metal content of the water sample. When detecting the chemical oxygen demand (COD), the analysis unit measures the amount of oxidant consumed by reducing substances in the water sample through a chemical reaction to evaluate the organic matter content; when detecting the heavy metal content, techniques such as atomic absorption spectrometry are used to determine the concentrations of elements such as lead, mercury, and cadmium.

[0038] After the detection is completed, the analysis unit transmits the data to the server. The server compares the detected data with the preset water quality standards, which are formulated according to different uses of rainwater reuse in port terminals. For example, the water quality standards for ground spraying and dust suppression are relatively low, while the standards for toilet flushing and landscape water use in the living area are relatively high. The server comprehensively analyzes various indicators to obtain the water quality assessment result and determines whether the rainwater meets the reuse standards.

[0039] When the water quality assessment result obtained by the server indicates that the bioretention purification is passed, that is, the rainwater in the target collection pool meets the reuse standards, the server configures the reclaimed water reuse task for the target collection pool.

[0040] The server arranges the reclaimed water for ground spraying and dust suppression according to the dust situation and weather data in the port area. In areas prone to dust generation such as the stacking area and loading and unloading area of the port terminal, when the weather is dry, the wind is strong, and the cargo handling is frequent, the server controls the spraying system to turn on, and evenly sprays the reclaimed water in the target collection pool on the ground through the nozzles to adsorb and settle the dust, improving the air quality and working environment in the port area.

[0041] The server introduces the reclaimed water in the target collection pool into the toilet pipeline system in the living area through the intelligent control system. When residents use the toilet to flush, the reclaimed water flows out of the pipeline to complete the flushing, realizing the recycling of water resources, reducing the dependence on fresh water resources, and reducing the sewage treatment pressure in the living area.

[0042] In the landscape area of the port terminal, such as gardens and artificial lakes, the server controls the supply of reclaimed water according to the water use requirements of the landscape area. In summer, the landscape plants require a large amount of water. The server controls the irrigation system to transport the reclaimed water to the garden to irrigate the plants; at the same time, replenish the artificial lake with reclaimed water through pipelines to maintain the water level and water quality of the lake and create a beautiful landscape environment.

[0043] For example, in summer, the dust in the stacking area of the port terminal is large, and the server starts the ground spraying task to suppress the dust; the residents in the living area normally use the reclaimed water to flush the toilet; the irrigation system in the landscape area uses the reclaimed water to water the flowers, and the artificial lake is replenished with the reclaimed water, realizing the efficient recycling of water resources and ensuring the sustainable development of the port terminal.

[0044] In summary, through the precise control and scientific management of each step of the bioretention purification method for rainwater collection and treatment at port terminals by the server, efficient rainwater collection, deep purification, and reasonable reuse are achieved, strongly supporting the sustainable development of port terminals.

[0045] In an embodiment of the present invention, the cross-section of the biological filter is arc-shaped; The vegetation layer is located on the side of the biological filter close to the ground. The vegetation layer is composed of preset port area plant species and is used to filter and intercept the substances not filtered by the grille carried in the runoff rainwater; The water distribution layer is located on the side of the vegetation layer away from the ground. The water distribution layer is filled with quartz sand and is used to filter and control the uniform infiltration of rainwater; The microbial filler layer is located on the side of the water distribution layer away from the vegetation layer. The microbial filler layer is composed of a combination of activated carbon particles inoculated with composite microbial membranes and inoculates corresponding functional microorganisms based on the characteristics of rain and sewage in different zones of the port area; The support layer is located on the side of the microbial filler layer away from the water distribution layer. The support layer is filled with gravel and is used to support the vegetation layer, the water distribution layer, and the microbial filler layer; The infiltration layer is located on the side of the support layer away from the microbial filler layer. The infiltration layer is filled with zeolite and is used to filter and adsorb pollutants.

[0046] In an embodiment of the present invention, by way of example, at a large comprehensive port terminal, the server is responsible for controlling the operation of the biological filter. The cross-section of this biological filter is arc-shaped, and this design can effectively reduce the scouring of rainwater runoff.

[0047] The side of the biological filter close to the ground is the vegetation layer. The server selects preset port area plant species to construct the vegetation layer according to conditions such as whether the port is located in an inland river or a seaport. For example, at a seaport terminal, salt-tolerant plants are selected. Whenever it rains, the rainwater carrying various pollutants flows into the biological filter after being preliminarily filtered by the grille from the yard. The vegetation layer plays a role in filtering and intercepting substances such as coal dust and fine ore particles that the grille fails to filter.

[0048] Below the vegetation layer is the water distribution layer, which is filled with quartz sand. When the rainwater passes through the vegetation layer and enters the water distribution layer, the quartz sand further filters the rainwater to remove finer impurities. At the same time, the water distribution layer controls the uniform infiltration of rainwater. Taking the biological filter corresponding to the dry bulk cargo yard as an example, when a large amount of rainwater flows in, the water distribution layer ensures that the rainwater is evenly distributed to the lower layer, avoiding local water flow concentration and ensuring the consistency of the purification effect.

[0049] Further down is the microbial filler layer, which is composed of a composite microbial membrane inoculated with activated carbon particles. The server inoculates this layer with corresponding functional microorganisms based on the characteristics of rainwater and sewage in different zones of the port area. For example, in the biofilter corresponding to the loading and unloading area, since the rainwater and sewage contain a large amount of oil, microorganisms that can degrade oil are inoculated. On the surface of the activated carbon particles, the microorganisms decompose and transform the pollutants in the rainwater, deeply purifying the water quality.

[0050] Below the microbial filler layer is the support layer, which is filled with gravel. The support layer shoulders the heavy responsibility of supporting the vegetation layer, water separation layer and microbial filler layer above to ensure the stability of the biofilter structure. Under long-term rainwater erosion and pressure from various layers, the support layer remains stable, ensuring the normal operation of the entire filter.

[0051] The bottom layer is the infiltration layer, which is filled with zeolite. After the rainwater has been treated in the previous layers, it flows into the infiltration layer. With its rich microporous structure, the zeolite performs the final filtration and adsorption of pollutants remaining in the rainwater, further improving the water quality and making the rainwater flowing out of the biofilter reach a higher standard, laying the foundation for subsequent entry into the target water collection pool and reuse.

[0052] In the embodiment of the present invention, the water quality of the target water collection pool is evaluated at preset time intervals to obtain a water quality evaluation result, which can be implemented through the following examples.

[0053] Performing feature extraction operations on water quality samples to be evaluated in a set of water quality samples to be evaluated at preset time intervals to obtain a water quality feature set, wherein the set of water quality samples to be evaluated includes a plurality of water quality samples to be evaluated for indicating different monitoring points of the target water collection pool, and the water quality feature set includes a plurality of water quality features arranged in a sequence of preset monitoring points; Performing water quality correlation analysis on the water quality feature set and the evaluation vector to obtain comprehensive water quality features, wherein the evaluation vector includes a plurality of evaluation unit parameters, and the evaluation unit parameters are used to indicate the water collection tank partition characteristics of the target water collection tank; Performing water quality assessment on the comprehensive water quality characteristics to obtain basic water quality assessment results; According to the basic water quality assessment result, the assessment unit parameters in the assessment vector are removed to obtain an optimized assessment vector; A water quality assessment result is obtained according to the optimized assessment vector and the water quality feature set.

[0054] In an embodiment of the present invention, exemplarily, the server starts the water quality assessment work at preset time intervals. It controls the sampling device to collect multiple water quality samples to be evaluated from different monitoring points of the target sump. These monitoring points are distributed at different positions in the sump, covering key areas such as the inlet, middle, and outlet, forming a set of water quality samples to be evaluated. Subsequently, the server performs feature extraction operations on each water quality sample in the set. For example, for the target sump into which the rainwater after dry bulk area treatment flows, the dust content, heavy metal content, etc. in the sample will be detected emphatically; for the samples related to the loading and unloading area, more attention will be paid to the oil content, etc. After extraction, a water quality feature set arranged in the order of preset monitoring points is obtained, which contains multiple water quality features.

[0055] Next, the server performs water quality correlation analysis on the water quality feature set and the evaluation vector. The evaluation vector contains multiple evaluation unit parameters, which are set according to the characteristics of different sump partitions of the target sump. For example, different partitions correspond to different functions, some are used to store preliminarily purified water, and some are close to the reuse end. The server analyzes the relationship between the water quality features and the parameters of each evaluation unit. For example, if a certain monitoring point is close to the edge of the sump, its water quality features interact with the evaluation unit parameters of the corresponding edge partition in the correlation analysis, and finally an integrated water quality feature is obtained.

[0056] The server conducts a water quality assessment on the integrated water quality feature. It judges whether the integrated water quality feature meets the standards according to various preset water quality standards, such as the pH value range, the upper limit of pollutant concentration, etc., so as to obtain the basic water quality assessment result. Assuming that the basic water quality assessment result shows that the water quality in some areas does not meet the standards in a certain aspect, the server will remove the evaluation unit parameters in the evaluation vector according to this result. For example, if it is found that the water quality in a certain corner of the sump is abnormal due to special reasons, the evaluation unit parameters corresponding to this corner may be removed to optimize the evaluation vector.

[0057] Finally, the server uses the optimized evaluation vector and the water quality feature set to conduct a comprehensive analysis again. It reconsiders the relationship between each water quality feature and the parameters in the optimized evaluation vector, so as to obtain a more accurate water quality assessment result. This result comprehensively reflects the water quality status of the target sump, providing a reliable basis for whether to enable the recycled water reuse task in the future.

[0058] In an embodiment of the present invention, the water quality correlation analysis of the water quality feature set and the evaluation vector to obtain the integrated water quality feature can be implemented through the following example.

[0059] According to the monitoring point position information represented by the water quality samples to be evaluated in the set of water quality samples to be evaluated, determine the target water quality feature and the target partition evaluation sub-vector corresponding to the target water quality feature from the water quality feature set; Perform a water quality correlation analysis on the target water quality characteristics and the target sub-vector of partition evaluation to obtain sub-characteristics of partition water quality; Obtain the comprehensive water quality characteristics based on multiple sub-characteristics of partition water quality.

[0060] In an embodiment of the present invention, exemplarily, the server works based on the location information of the monitoring points represented by each water quality sample to be evaluated in the set of water quality samples to be evaluated. For example, in a target sump, monitoring points at different positions correspond to different functional areas, such as a monitoring point near the rainwater inflow end of the container stacking area, a monitoring point near the reuse end of the living area, etc. The server determines, for each monitoring point location, the corresponding target water quality characteristics from the set of water quality characteristics. For example, for a monitoring point near the rainwater inflow end of the container stacking area, its target water quality characteristics may focus on the content of solid suspended matter, residual specific pollutants, etc.; at the same time, it determines the target sub-vector of partition evaluation corresponding to the target water quality characteristics. This sub-vector includes evaluation unit parameters related to the partition where the monitoring point is located, such as special requirements for water quality in this partition, characteristics of past water quality data, etc.

[0061] Subsequently, the server performs a water quality correlation analysis on the determined target water quality characteristics and the target sub-vector of partition evaluation. Taking a monitoring point near the dry bulk cargo stacking area as an example, the dust content in its target water quality characteristics is relatively high, and the filtering requirements and acceptable ranges for dust in the target sub-vector of partition evaluation are clear. The server analyzes the relationship between the dust content and these requirements and ranges, and at the same time considers the mutual influence of other relevant water quality indicators and evaluation parameters, so as to obtain the sub-characteristics of partition water quality in this partition. This sub-characteristic comprehensively reflects the water quality characteristics of the partition where the monitoring point is located.

[0062] The server performs the above operations on all monitoring points to obtain multiple sub-characteristics of partition water quality. Then, the server comprehensively considers these sub-characteristics of partition water quality. For example, the sub-characteristics of partition water quality near different functional areas are integrated according to certain weights. The sub-characteristics of partition water quality of the monitoring point near the rainwater source may have a relatively large weight, while the sub-characteristics of partition water quality of the monitoring point near the reuse end have a relatively small weight. In this way, the server finally obtains the comprehensive water quality characteristics, which comprehensively and meticulously reflect the overall water quality status of the target sump, providing a solid data basis for subsequent water quality evaluation and reuse decision-making.

[0063] In an embodiment of the present invention, the performing a water quality correlation analysis on the target water quality characteristics and the target sub-vector of partition evaluation to obtain sub-characteristics of partition water quality can be implemented through the following example.

[0064] Use the target water quality characteristics as the characteristic reference parameters and the characteristic weight parameters respectively, and use the target sub-vector of partition evaluation as the evaluation condition parameters to perform water quality correlation mapping processing to obtain the sub-characteristics of partition water quality.

[0065] In an embodiment of the present invention, exemplarily, the server determines the target water quality characteristics and the corresponding target sub-vector for zonal evaluation from the water quality samples to be evaluated collected at different monitoring points. Taking the target sump monitoring point corresponding to the port loading and unloading area as an example, the target water quality characteristics may be the oil content in rainwater, the size and concentration of cargo debris particles, etc. The target sub-vector for zonal evaluation includes evaluation condition parameters such as the acceptable standards for oil and debris in rainwater in this loading and unloading area, and the expected purification degree of the treatment process.

[0066] Next, the server starts the water quality association mapping process. It uses the target water quality characteristics as the characteristic reference parameter and the characteristic weight parameter respectively. For example, for the target water quality characteristic of oil content, on the one hand, it is used as the characteristic reference parameter, representing the actual oil content level in the current rainwater, which is the basic data for judging the water quality condition; on the other hand, it is used as the characteristic weight parameter. Since the loading and unloading area is sensitive to oil and the oil content has a greater impact on the overall water quality, a higher weight is assigned to it.

[0067] Then, the server uses the target sub-vector for zonal evaluation as the evaluation condition parameter. For example, the loading and unloading area stipulates that the oil content in rainwater must be lower than a certain threshold, and there are also corresponding standards for the size and concentration of cargo debris particles, which constitute the evaluation condition parameters. The server compares and analyzes the characteristic reference parameter (actual oil content, etc.) with the evaluation condition parameter (specified oil threshold, etc.), and also considers the characteristic weight parameter (high weight of oil). If the actual oil content is close to or exceeds the threshold, and due to its high weight, then under comprehensive consideration, the impact on the zonal water quality is greater.

[0068] Through such a water quality association mapping process, the server comprehensively and meticulously analyzes the relationship between the target water quality characteristics and the target sub-vector for zonal evaluation, and finally obtains the zonal water quality sub-characteristics of the loading and unloading area where the monitoring point is located. These zonal water quality sub-characteristics comprehensively reflect the relationship between various pollutants in rainwater in this area and the evaluation standards, accurately reflecting the water quality condition of this area, and providing key data support for the subsequent formation of comprehensive water quality characteristics and overall water quality evaluation.

[0069] In an embodiment of the present invention, the basic water quality evaluation result includes a plurality of basic pollution category probabilities and a plurality of basic pollution zonal identifiers that have a mapping relationship with the plurality of basic pollution category probabilities, and the plurality of basic pollution zonal identifiers have a mapping relationship with a plurality of evaluation unit parameters in the evaluation vector; Removing the evaluation unit parameters in the evaluation vector according to the basic water quality evaluation result to obtain an optimized evaluation vector can be implemented through the following example.

[0070] For each of the said basic pollution zone identifiers, determine the evaluation unit parameters to be removed corresponding to the basic pollution zone identifier from the said evaluation vector; According to the basic pollution category probability corresponding to the basic pollution zone identifier and the pollution determination threshold, determine the parameter removal determination of the evaluation unit parameters to be removed; According to a plurality of the said parameter removal determinations, remove the evaluation unit parameters in the evaluation vector to obtain the optimized evaluation vector.

[0071] In an embodiment of the present invention, by way of example, taking the target sump of a certain port terminal as an example, the basic water quality evaluation result shows that, for example, under the basic pollution zone identifier corresponding to the dry bulk cargo yard area, the probability of coal dust pollution category is 80%, and under the basic pollution zone identifier corresponding to the loading and unloading area, the probability of oil pollution category is 70%, etc.

[0072] Next, the server removes the evaluation unit parameters in the evaluation vector according to the basic water quality evaluation result to obtain the optimized evaluation vector.

[0073] For each basic pollution zone identifier, the server determines the evaluation unit parameters to be removed corresponding thereto from the evaluation vector. For example, for the basic pollution zone identifier corresponding to the dry bulk cargo yard area, the evaluation unit parameters to be removed corresponding thereto in the evaluation vector may include parameters related to coal dust treatment, such as the expected purification rate of the sump in this area for coal dust, the treatment capacity of a specific filter layer for coal dust, etc.

[0074] Then, the server determines the parameter removal determination of the evaluation unit parameters to be removed according to the basic pollution category probability corresponding to the basic pollution zone identifier and the pollution determination threshold. Suppose the pollution determination threshold is set at 60%. For the dry bulk cargo yard area, the basic pollution category probability is 80%, which is higher than the threshold, indicating that the coal dust pollution situation is relatively serious. The evaluation unit parameters to be removed corresponding thereto may be determined to be removed because the current treatment parameters fail to effectively control the pollution; while for a certain zone, the basic pollution category probability is 50%, which is lower than the threshold, and the evaluation unit parameters to be removed corresponding thereto may be determined not to be removed.

[0075] The server comprehensively makes a plurality of parameter removal determinations and removes the evaluation unit parameters in the evaluation vector. For example, according to the determination results of each zone, remove the evaluation unit parameters determined to be removed in the evaluation vector, and finally obtain the optimized evaluation vector. This optimized evaluation vector is more in line with the actual water quality situation of the current target sump, laying a foundation for obtaining a more accurate water quality evaluation result by combining with the water quality characteristic set, and helping to make a more scientific decision on whether the rainwater is suitable for reuse and how to further optimize the treatment process.

[0076] In an embodiment of the present invention, the basic water quality assessment result includes a plurality of basic pollution category probabilities and a plurality of basic pollution zone identifiers that have a mapping relationship with the plurality of basic pollution zone identifiers, and the plurality of basic pollution zone identifiers have a mapping relationship with a plurality of evaluation unit parameters in the evaluation vector; Removing the evaluation unit parameters in the evaluation vector according to the basic water quality assessment result to obtain an optimized evaluation vector can be implemented through the following examples.

[0077] Determine a sub-vector of the partition to be removed corresponding to the preset monitoring area in the target sump from the evaluation vector; According to the plurality of basic pollution zone identifiers, determine a specified number of target basic pollution category probabilities corresponding to the preset monitoring area from the plurality of basic pollution category probabilities; Remove the evaluation unit parameters in the sub-vector of the partition to be removed according to the basic pollution zone identifiers of the specified number of target basic pollution category probabilities to obtain the optimized sub-vector of the partition evaluation; Obtain the optimized evaluation vector according to a plurality of the optimized sub-vectors of the partition evaluation.

[0078] In an embodiment of the present invention, by way of example, in the rainwater collection and treatment system of a certain port terminal, the server undertakes the key tasks of water quality assessment and related parameter optimization. The basic water quality assessment result includes a plurality of basic pollution category probabilities and a plurality of basic pollution zone identifiers mapped thereto, and these basic pollution zone identifiers have a mapping relationship with a plurality of evaluation unit parameters in the evaluation vector.

[0079] The server first determines a sub-vector of the partition to be removed corresponding to the preset monitoring area in the target sump from the evaluation vector. Suppose the target sump is divided into a plurality of preset monitoring areas, such as Area A near the dry bulk cargo yard area, Area B near the loading and unloading area, etc. Taking Area A as an example, the server identifies a series of evaluation unit parameters related to Area A in the evaluation vector to form a sub-vector of the partition to be removed, and these parameters may involve the treatment expectations and purification standards after the rainwater from the dry bulk cargo yard area flows into the target sump.

[0080] Next, based on multiple basic pollution zone identifiers, the server determines a specified number of target basic pollution category probabilities corresponding to the preset monitoring area from multiple basic pollution category probabilities. For example, the basic pollution categories include coal dust pollution, oil pollution, heavy metal pollution, etc. For area A, the server, according to its basic pollution zone identifier, finds the target basic pollution category probabilities corresponding to the specific pollution level related to this area from among numerous basic pollution category probabilities. Assuming the specified pollution level is the "high pollution level" and the main pollutant in area A is coal dust, the server determines the target basic pollution category probability of coal dust pollution at the high pollution level.

[0081] Then, according to the basic pollution zone identifiers of each of the specified number of target basic pollution category probabilities, the server removes the evaluation unit parameters in the sub-vector of the partition to be removed for evaluation, thereby obtaining an optimized sub-vector of the partition for evaluation. For example, the basic pollution zone identifier corresponding to coal dust pollution clarifies the processing parameters related to area A. If the pollution probability indicates poor processing effects, the server removes the evaluation unit parameters in the sub-vector of the partition to be removed for evaluation that are related to the unsatisfactory processing effects of coal dust, such as unreasonable filter layer settings, too low adsorbent dosage standards, etc., to form an optimized sub-vector of the partition for evaluation.

[0082] The server performs the above operations for each preset monitoring area to obtain multiple optimized sub-vectors of the partition for evaluation. Finally, by integrating these optimized sub-vectors of the partition for evaluation, an optimized evaluation vector is obtained. This optimized evaluation vector can more accurately reflect the actual water quality conditions of each area of the target sump, providing strong support for more accurate water quality assessment in combination with the water quality characteristic set later, and helping the port terminal to more scientifically plan rainwater reuse and treatment strategies.

[0083] In the embodiment of the present invention, obtaining the water quality assessment result according to the optimized evaluation vector and the water quality characteristic set can be implemented through the following example.

[0084] According to the optimized evaluation vector and the water quality characteristic set, obtain the target comprehensive water quality characteristic; Perform water quality assessment on the target comprehensive water quality characteristic to obtain the water quality assessment result.

[0085] In an embodiment of the present invention, by way of example, in a rainwater collection and treatment system for a port terminal, the server derives a target comprehensive water quality characteristic based on the optimized evaluation vector and the water quality characteristic set. Taking a certain port terminal as an example, it is assumed that the optimized evaluation vector has been adjusted according to the water quality requirements and treatment expectations for different areas (such as living areas, loading and unloading areas, stacking areas, etc.). The water quality characteristic set includes various water quality characteristics analyzed from samples collected at different monitoring points of the target sump, such as the microbial content at the living area monitoring point, the oil pollution concentration at the loading and unloading area monitoring point, and the dust particle size at the stacking area monitoring point.

[0086] The server correlates the optimized evaluation vector with the water quality characteristic set. For example, for the loading and unloading area, the optimized evaluation vector emphasizes strict standards for oil pollution treatment. The server then focuses on the oil pollution concentration-related characteristics of the monitoring point in the loading and unloading area in the water quality characteristic set. It comprehensively analyzes the relationship between the oil pollution concentration and parameters such as the acceptable range specified in the evaluation vector and the expected effect of the treatment process, and at the same time combines other relevant water quality characteristics, such as the content of other chemical substances that may accompany the oil pollution. Through this comprehensive and detailed analysis, the target comprehensive water quality characteristic reflecting the overall water quality of the entire target sump is integrated. This target comprehensive water quality characteristic is no longer a simple list of the water quality characteristics of each individual monitoring point in isolation, but a comprehensive manifestation that takes into account the functional requirements of different areas, treatment expectations, and the mutual influence of various water quality characteristics.

[0087] The server conducts a water quality assessment on the target comprehensive water quality characteristic to obtain the final water quality assessment result. The server compares the target comprehensive water quality characteristic with various preset water quality standards. These standards cover a series of indicators from pH value to the concentration of various pollutants. For example, for the standard of using recycled rainwater in the port for landscape water, the server checks whether each indicator in the target comprehensive water quality characteristic meets this standard. If all indicators are within the standard range, it is determined that the water quality meets the standard; if some indicators exceed the standard, such as the oil pollution concentration in the loading and unloading area being higher than the maximum value allowed for landscape water, the server will clearly indicate the exceeded items and the degree. The finally obtained water quality assessment result will provide a key basis for whether the port terminal can safely and effectively reuse this rainwater, and at the same time provide an important reference for further optimizing the rainwater treatment process.

[0088] In an embodiment of the present invention, obtaining the target comprehensive water quality characteristic according to the optimized evaluation vector and the water quality characteristic set can be implemented through the following example.

[0089] Perform pollution characteristic interaction processing on the optimized evaluation vector to obtain a target evaluation vector; and Perform water quality correlation analysis on the target evaluation vector and the water quality characteristic set to obtain the target comprehensive water quality characteristic.

[0090] In an embodiment of the present invention, exemplarily, the server performs pollution feature interaction processing on the optimized evaluation vector to generate a target evaluation vector. For example, at a certain port terminal, the optimized evaluation vector includes evaluation unit parameters for different regions (such as container stacking areas, dry bulk cargo stacking areas, loading and unloading areas, etc.), and these parameters reflect the treatment requirements and expectations for different pollutions in each region. The server will analyze the mutual influence between the pollution characteristics of each region. Suppose the main pollution in the dry bulk cargo stacking area is coal dust, and the loading and unloading area may generate oil pollution due to cargo handling. At the same time, the loading and unloading area is close to the dry bulk cargo stacking area, and the coal dust may be mixed with the oil pollution. The server will consider this potential pollution mixing situation and adjust the evaluation unit parameters corresponding to the dry bulk cargo stacking area and the loading and unloading area in the evaluation vector. For example, when adjusting the oil pollution treatment parameters for the loading and unloading area, considering the impact of the possible mixed coal dust on the oil pollution treatment process, the consideration factor for the treatment effect of the mixed pollutants is increased, so as to obtain a target evaluation vector that can better reflect the actual pollution interaction situation.

[0091] The server performs water quality correlation analysis on the target evaluation vector and the water quality feature set to obtain the target comprehensive water quality feature. The water quality feature set is obtained by collecting samples from different monitoring points of the target sump and includes various water quality features of each region. Taking the water quality features of the monitoring point in the container stacking area as an example, there may be the chemical substance content of the cargo residue and the concentration of fine particles carried by rainwater. The server correlates each parameter in the target evaluation vector with the corresponding feature in the water quality feature set. For example, the parameter for treating the chemical substance of the cargo residue in the container stacking area in the target evaluation vector is compared and analyzed with the chemical substance content of the cargo residue at the monitoring point in this area in the water quality feature set. Analyze the gap between the actual content of this chemical substance and the treatment expectation in the evaluation vector, and at the same time consider the influence of other relevant water quality features on it, such as the adsorption or reaction effect of fine particles on the chemical substance. Through the comprehensive and detailed correlation analysis of all relevant features in the target evaluation vector and the water quality feature set, the target comprehensive water quality feature reflecting the actual water quality condition of the entire target sump and the mutual relationship of each pollution factor is comprehensively obtained. This target comprehensive water quality feature comprehensively considers the pollution interaction in different regions and the actual water quality situation, providing a solid data basis for subsequent accurate water quality evaluation.

[0092] In an embodiment of the present invention, the obtaining of the target comprehensive water quality feature according to the optimized evaluation vector and the water quality feature set can be implemented through the following examples.

[0093] In the case where it is determined that the current cycle is less than the preset number of cycles, perform pollution feature interaction processing on the target evaluation vector of the previous cycle to obtain the target evaluation vector of the current cycle; Perform water quality correlation analysis on the target evaluation vector of the current cycle and the comprehensive water quality feature of the previous cycle to obtain the comprehensive water quality feature of the current cycle; and When it is determined that the current cycle is equal to the preset number of cycles, determine the target comprehensive water quality characteristics according to the comprehensive water quality characteristics of the current cycle.

[0094] In an embodiment of the present invention, by way of example, assume that a water quality assessment cycle is set for a port terminal. The server first determines whether the current cycle is less than the preset number of cycles. For example, the preset number of cycles is 5. When the server determines that the current is in the 3rd cycle, the condition that the current cycle is less than the preset number of cycles is satisfied. At this time, the server performs pollution characteristic interaction processing on the target evaluation vector of the previous cycle (the 2nd cycle). In the target evaluation vector of the previous cycle, evaluation parameters for various pollution characteristics have been included for different regions (such as living areas, stacking areas, loading and unloading areas, etc.). The server will further analyze the mutual influence between these pollution characteristics according to the actual situation. For example, the dust from the goods in the stacking area may spread to the living area with the airflow, affecting the air quality in the living area and further affecting the pollutant components in the rainwater. The server will comprehensively consider these factors and adjust the evaluation parameters of the relevant regions in the target evaluation vector of the previous cycle to obtain the target evaluation vector of the current cycle.

[0095] Next, the server performs water quality correlation analysis on the target evaluation vector of the current cycle and the comprehensive water quality characteristics of the previous cycle (the 2nd cycle). The comprehensive water quality characteristics of the previous cycle are a comprehensive reflection of the overall water quality status of the target sump at that time, covering the water quality characteristics of each monitoring point and the mutual relationship between the pollution characteristics of different regions. The server carefully compares and analyzes the evaluation parameters in the target evaluation vector of the current cycle with each index in the comprehensive water quality characteristics of the previous cycle. For example, for the loading and unloading area, the requirement for the oil pollution treatment effect in the target evaluation vector of the current cycle may be adjusted. The server will check the actual content, distribution of the oil pollution in the loading and unloading area in the comprehensive water quality characteristics of the previous cycle and its interaction with other pollutants, and analyze the difference between the current requirement and the actual water quality to obtain the comprehensive water quality characteristics of the current cycle.

[0096] When the server determines that the current cycle is equal to the preset number of cycles (such as the current is in the 5th cycle), it determines the target comprehensive water quality characteristics according to the comprehensive water quality characteristics of the current cycle. After analysis and adjustment in multiple cycles, the comprehensive water quality characteristics of the current cycle have fully considered the changes in the pollution characteristics of each region of the port terminal in different cycles and their mutual influence. The server determines this comprehensive water quality characteristics of the current cycle as the target comprehensive water quality characteristics. This target comprehensive water quality characteristics comprehensively and accurately reflects the overall water quality status of the target sump within the preset cycle, provides a key basis for subsequent water quality assessment, and helps the port terminal make scientific decisions on the rainwater reuse and treatment plan.

[0097] In the embodiments of the present invention, for the water quality assessment of the target comprehensive water quality characteristics to obtain the water quality assessment result, the following examples can be used for implementation.

[0098] Determine the pollution type of the target comprehensive water quality characteristics to obtain the pollution category probability; Determine the pollution area of the target comprehensive water quality characteristics to obtain the pollution area identifier; and Obtain the water quality assessment result according to the pollution category probability and the pollution area identifier.

[0099] In the embodiments of the present invention, for example, the server determines the pollution type of the target comprehensive water quality characteristics, thereby obtaining the pollution category probability. Suppose the target comprehensive water quality characteristics include various water quality data obtained from monitoring points in different areas of the target sump, covering various aspects of information such as pH value, chemical oxygen demand, various heavy metal contents, and oil pollution concentration. The server deeply analyzes these data based on preset algorithms and databases. For example, for the target sump of a certain port terminal, the server analyzes and finds that in the water quality data of the monitoring point near the loading and unloading area, the oil pollution-related indicators are particularly prominent. After comparing with a large amount of historical data and standard pollution type characteristics, the server determines that the probability of oil pollution in this area is 80%. At the same time, due to the possible generation of other pollutants during the cargo loading and unloading process, it is also determined that the probability of trace heavy metal pollution is 20%. In this way, the server obtains the pollution category probability corresponding to different pollution types.

[0100] The server determines the pollution area of the target comprehensive water quality characteristics and obtains the pollution area identifier. The target sump corresponds to different functional areas of the port terminal, such as the living area, stacking area, loading and unloading area, etc. The server determines the pollution area based on the association between each monitoring point in the water quality characteristics and different functional areas, as well as the characteristics of common pollution types in different areas. For example, based on the location information of the monitoring point and the characteristics of the water quality data, the server confirms that at the monitoring point corresponding to the dry bulk cargo stacking area, the water quality characteristics show that the main pollutant is coal dust, which conforms to the common pollution type in this area. Therefore, this area is marked as "Dry Bulk Cargo Stacking Area - Dust Pollution Area", which is a pollution area identifier. By analyzing all monitoring points, the server determines the identifiers of each pollution area.

[0101] Based on the obtained pollution category probability and pollution zone identifier, the server derives the water quality assessment result. For example, after the loading and unloading area is determined to be a high-probability oil pollution area, the server combines this pollution category probability with the corresponding pollution zone identifier. If the port has clear water quality standards and treatment requirements for different pollution types in different areas, for the oil pollution in the loading and unloading area, it is stipulated that if the oil pollution probability exceeds 60%, enhanced treatment measures need to be taken. Then, based on this standard and combining the determined oil pollution probability of 80% in the loading and unloading area, the server concludes that the water quality in the loading and unloading area does not meet the ideal standard and an enhanced oil treatment evaluation result is required. By performing similar analyses on all pollution zone identifiers and their corresponding pollution category probabilities, the server finally forms a comprehensive and accurate water quality assessment result, providing a key basis for the port terminal to take targeted rainwater treatment measures and reasonably reuse rainwater in the future.

[0102] In an embodiment of the present invention, for the water quality assessment of the comprehensive water quality characteristics to obtain the basic water quality assessment result, the following example can be executed for implementation.

[0103] Determine the pollution type of the comprehensive water quality characteristics to obtain the basic pollution category probability; Determine the pollution zone of the comprehensive water quality characteristics to obtain the basic pollution zone identifier; Based on the basic pollution category probability and the basic pollution zone identifier, obtain the basic water quality assessment result.

[0104] In an embodiment of the present invention, exemplarily, the server conducts a pollution type determination on the comprehensive water quality characteristics to obtain the basic pollution category probability. Taking a large comprehensive port terminal as an example, the comprehensive water quality characteristic data is derived from the analysis of samples collected at different positions and different times in the target sump, including numerous water quality parameters such as the content of different chemical substances and microbial indicators. The server uses built-in algorithms and professional databases for in-depth analysis. For example, at the monitoring point near the liquid chemical loading and unloading area, the water quality data shows that the concentration of certain specific chemical substances is abnormal. The server compares these data with the standard characteristics of various pollution types, and after complex calculations, determines that the probability of chemical pollution in this area is 75%, and at the same time, due to the possible introduction of other impurities during loading and unloading operations, the probability of micro-particle pollution is determined to be 25%, thus clarifying the basic pollution category probability.

[0105] The server conducts pollution zoning determination on the comprehensive water quality characteristics to obtain the basic pollution zoning identifier. The target sump of the port terminal is associated with multiple functional areas, such as the living area, container stacking area, dry bulk cargo stacking area, loading and unloading area, etc. The server divides the pollution areas based on the geographical location of each monitoring point and the pollution sources and characteristics reflected by the water quality characteristics. For example, at the monitoring point near the living area, the water quality characteristics mainly reflect the pollutants related to domestic sewage. Based on this, the server marks this area as the "living area - domestic sewage pollution area", which is a basic pollution zoning identifier. By analyzing each monitoring point one by one, the server determines all the basic pollution zoning identifiers.

[0106] Based on the obtained basic pollution category probabilities and basic pollution zoning identifiers, the server generates the basic water quality assessment results. For example, in the dry bulk cargo stacking area, the server determines that the probability of coal dust pollution in this area is 80%, corresponding to the basic pollution zoning identifier of "dry bulk cargo stacking area - coal dust pollution area". If the port has set clear standards for this type of pollution in this area, such as starting an additional dust reduction and purification process when the probability of coal dust pollution exceeds 60%. Based on this standard and combined with the determination situation in the dry bulk cargo stacking area, the server obtains the basic water quality assessment result that the water quality in this area needs additional dust reduction and purification treatment. Through a detailed analysis of each basic pollution zoning identifier and its corresponding basic pollution category probability, the server comprehensively and accurately generates the basic water quality assessment results, providing important data support for subsequent optimization of the assessment vector and obtaining the final water quality assessment result.

[0107] In the embodiment of the present invention, the following implementation manners are also provided.

[0108] Perform pollution feature interaction processing on the basic assessment vector to obtain the assessment vector, where the basic assessment vector includes multiple dynamically adjustable assessment unit parameters, and the dynamically adjustable assessment unit parameters are trained through a historical water quality sample set and the pollution level annotations corresponding to the historical water quality sample set.

[0109] In the embodiment of the present invention, exemplarily, the server first obtains the basic assessment vector, which includes multiple dynamically adjustable assessment unit parameters. These parameters are not fixed, but are obtained through training on the historical water quality sample set and the corresponding pollution level annotations. For example, the port terminal has long accumulated a large amount of rainwater water quality sample data from various areas such as the living area, stacking area, and loading and unloading area in different seasons and weather conditions, which constitutes the historical water quality sample set. At the same time, the staff has marked the corresponding pollution levels for each sample according to the actual pollution situation, such as mild pollution, moderate pollution, severe pollution, etc.

[0110] The server uses this data for training. During the training process, it analyzes the relationships between various water quality indicators and pollution levels in the historical water quality sample set. For example, in the historical samples of the loading and unloading area, it is found that there is a certain correlation law between the oil content, the amount of cargo debris, and the pollution level. When both the oil content and the amount of cargo debris are relatively high, it often corresponds to a higher pollution level. By learning a large amount of similar data, the server determines the initial values of the parameters of each dynamically adjustable evaluation unit, and these parameters can initially reflect the relationship between the water quality in different areas and the pollution level.

[0111] The server performs pollution feature interaction processing on the basic evaluation vector to obtain the final evaluation vector. In the actual operation of the port terminal, the pollution characteristics of different areas do not exist in isolation but interact with each other. For example, the coal dust in the dry bulk cargo stacking area may drift to the nearby loading and unloading area along with the air flow and mix with the oil pollution in the loading and unloading area, thus changing the pollution characteristics. The server takes into account this interaction of pollution characteristics and adjusts the parameters of the dynamically adjustable evaluation unit in the basic evaluation vector. For the parameters corresponding to the dry bulk cargo stacking area and the loading and unloading area, the server will recalculate and adjust the parameters according to the possible pollution interaction relationship between the two. For example, increase the weight of the relevant parameters considering the treatment effect of the mixed pollutants, so that the evaluation vector can more accurately reflect the actual pollution situation. After such processing, the server obtains the evaluation vector, which fully considers the interaction of pollution characteristics in each area of the port terminal and the law of historical water quality data, provides a more practical basis for subsequent water quality correlation analysis, water quality assessment, etc., helps to more accurately evaluate the water quality of the target sump, and provides strong support for the decision-making of rainwater treatment and reuse in the port terminal.

[0112] Please refer to Figure 3 , Figure 3 A bioretention purification device 110 for rainwater collection and treatment in a port terminal provided by an embodiment of the present invention, comprising: A purification module 1101, configured to collect rainwater from the drainage ditch of the port yard that has been preliminarily filtered by a grille through a rainwater collection pipe; deeply purify the rainwater through a biological filter pool, and store the deeply purified rainwater in a target sump through a water collection pipe; the biological filter pool includes a vegetation layer, a water distribution layer, a microbial filler layer, a supporting layer, and a percolation layer; An evaluation module 1102, configured to perform water quality evaluation on the target sump at a preset time interval to obtain a water quality evaluation result; and configure a reclaimed water reuse task for the target sump when the water quality evaluation result indicates that the bioretention purification has passed.

[0113] It should be noted that the implementation principle of the above-mentioned bioretention purification device 110 for rainwater collection and treatment in port terminals can refer to the implementation principle of the above-mentioned bioretention purification method for rainwater collection and treatment in port terminals, which will not be elaborated here. It should be understood that the division of each module of the above device is only a division of logical functions. In actual implementation, it can be fully or partially integrated into a physical entity, or physically separated. And these modules can all be implemented in the form of software called by a processing element; they can also all be implemented in the form of hardware; or some modules can be implemented in the form of software called by a processing element, and some modules can be implemented in the form of hardware. For example, the bioretention purification device 110 for rainwater collection and treatment in port terminals can be a separately established processing element, or can be integrated in a certain chip of the above device. In addition, it can also be stored in the memory of the above device in the form of program code, and the function of the above bioretention purification device 110 for rainwater collection and treatment in port terminals can be called and executed by a certain processing element of the above device. The implementation of other modules is similar. In addition, all or part of these modules can be integrated together or can be independently implemented. The processing element described here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed by the integrated logic circuit in the processor element or the instruction in the form of software.

[0114] For example, the above modules can be one or more integrated circuits configured to implement the above method, such as: one or more application specific integrated circuits (ASICs), or, one or more digital signal processors (DSPs), or, one or more field programmable gate arrays (FPGAs), etc. Again, when a certain module above is implemented in the form of a processing element scheduling program code, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processors that can call program code. Again, these modules can be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0115] An embodiment of the present invention provides a computer device 100. The computer device 100 includes a processor and a non-volatile memory storing computer instructions. When the computer instructions are executed by the processor, the computer device 100 executes the aforementioned bioretention purification device 110 for rainwater collection and treatment in port terminals. As Figure 4 shown, Figure 4The computer device 100 provided in the embodiment of the present invention is a structural block diagram. The computer device 100 includes a biological retention purification device 110 for collecting and treating rainwater at a port terminal, a memory 111, a processor 112 and a communication unit 113.

[0116] In order to realize data transmission or interaction, the memory 111, the processor 112 and the communication unit 113 are electrically connected to each other directly or indirectly. For example, the electrical connection between these components can be realized through one or more communication buses or signal lines. The biological retention and purification device 110 for collecting and treating rainwater at port terminals includes at least one software function module that can be stored in the memory 111 in the form of software or firmware or fixed in the operating system (OS) of the computer device 100. The processor 112 is used to execute the biological retention and purification device 110 for collecting and treating rainwater at port terminals stored in the memory 111, such as the software function modules and computer programs included in the biological retention and purification device 110 for collecting and treating rainwater at port terminals.

[0117] An embodiment of the present invention provides a readable storage medium, which includes a computer program. When the computer program is running, it controls the computer device where the readable storage medium is located to execute the aforementioned biological retention and purification device 110 for collecting and treating rainwater at a port terminal.

[0118] For illustrative purposes, the foregoing description is made with reference to specific embodiments. However, the above illustrative discussion is not intended to be exhaustive or to limit the present disclosure to the precise form disclosed. Numerous modifications and variations are possible in accordance with the above teachings. These embodiments are selected and described in order to best illustrate the principles of the present disclosure and its practical application, so that those skilled in the art can best utilize the present disclosure and utilize various embodiments with different modifications to suit the intended specific application.

Claims

1. A bioretention purification method for collecting and treating rainwater at ports and docks, characterized in that: include: The rainwater from the port yard drainage ditch that has been initially filtered by the grating is collected through the rainwater collection pipe; The rainwater collection pipe Deeply purify rainwater through a biofilter, and store the deeply purified rainwater in a target water collection tank through a water collection pipe; the biofilter includes a vegetation layer, a water separation layer, a microbial filler layer, a support layer, and a percolation layer; Performing water quality assessment on the target water collection pool at preset time intervals to obtain a water quality assessment result; When the water quality assessment result indicates that the bioretention purification has passed, a reclaimed water reuse task is configured for the target water collection pool.

2. The method according to claim 1, characterized in that The cross section of the biofilter is arc-shaped; The vegetation layer is located on the side of the biofilter tank close to the ground, and the vegetation layer is composed of the preset port area background plant species, and the vegetation layer is used to filter and intercept the runoff rainwater and the substances not filtered by the grille; The water diversion layer is located on the side of the vegetation layer away from the ground, the water diversion layer is filled with quartz sand, and the water diversion layer is used to filter and control the uniform infiltration of rainwater; The microbial filler layer is located on the side of the water-dividing layer away from the vegetation layer. The microbial filler layer is composed of a composite microbial membrane inoculated with activated carbon particles. The microbial filler layer is inoculated with corresponding functional microorganisms based on the characteristics of rainwater and sewage in different zones of the port area. The supporting layer is located on a side of the microbial filler layer away from the water-dividing layer, the supporting layer is filled with gravel, and the supporting layer is used to support the vegetation layer, the water-dividing layer, and the microbial filler layer; The infiltration layer is located on a side of the support layer away from the microbial filler layer. The infiltration layer is filled with zeolite and is used for filtering and adsorbing pollutants.

3. The method according to claim 1, characterized in that The step of evaluating the water quality of the target water collection pool at a preset time interval to obtain a water quality evaluation result includes: Performing feature extraction operations on water quality samples to be evaluated in a set of water quality samples to be evaluated at preset time intervals to obtain a water quality feature set, wherein the set of water quality samples to be evaluated includes a plurality of water quality samples to be evaluated for indicating different monitoring points of the target water collection pool, and the water quality feature set includes a plurality of water quality features arranged in a sequence of preset monitoring points; Determining a target water quality feature and a target partition evaluation subvector corresponding to the target water quality feature from the water quality feature set according to the monitoring point location information represented by the water quality sample to be evaluated in the water quality sample set to be evaluated; The target water quality characteristics are used as characteristic reference parameters and characteristic weight parameters respectively, and the target partition evaluation sub-vector is used as an evaluation condition parameter to perform water quality association mapping processing to obtain the partition water quality sub-characteristics; Obtaining a comprehensive water quality feature according to the plurality of water quality sub-features of the partitions, wherein the evaluation vector comprises a plurality of evaluation unit parameters, and the evaluation unit parameters are used to indicate the water collection tank partition features of the target water collection tank; Determine the pollution type of the comprehensive water quality characteristics to obtain the basic pollution category probability; Conduct pollution zoning determination on the comprehensive water quality characteristics to obtain basic pollution zoning identification; Obtaining the basic water quality assessment result according to the basic pollution category probability and the basic pollution zone identification; According to the basic water quality assessment result, the assessment unit parameters in the assessment vector are removed to obtain an optimized assessment vector; A water quality assessment result is obtained according to the optimized assessment vector and the water quality feature set.

4. The method according to claim 3, characterized in that The basic water quality assessment result includes a plurality of basic pollution category probabilities and a plurality of basic pollution partition identifiers that are mapped to the plurality of basic pollution category probabilities, and the plurality of basic pollution partition identifiers are mapped to a plurality of assessment unit parameters in the assessment vector; The step of removing the evaluation unit parameters in the evaluation vector according to the basic water quality evaluation result to obtain an optimized evaluation vector includes: For each of the basic pollution partition identifiers, determining from the evaluation vector a parameter of an evaluation unit to be removed corresponding to the basic pollution partition identifier; Determining a parameter elimination judgment of the evaluation unit parameter to be removed according to the basic pollution category probability and the pollution judgment threshold corresponding to the basic pollution partition identifier; According to the plurality of parameter elimination determinations, the evaluation unit parameters in the evaluation vector are removed to obtain the optimized evaluation vector.

5. The method according to claim 3, characterized in that: The basic water quality assessment result includes a plurality of basic pollution category probabilities and a plurality of basic pollution partition identifiers that are mapped to the plurality of basic pollution partition identifiers, and the plurality of basic pollution partition identifiers are mapped to a plurality of assessment unit parameters in the assessment vector; The step of removing the evaluation unit parameters in the evaluation vector according to the basic water quality evaluation result to obtain an optimized evaluation vector includes: Determine, from the evaluation vector, an evaluation subvector of a partition to be removed corresponding to a preset monitoring area in the target water collection pool; According to the multiple basic pollution zone identifiers, determine a designated number of target basic pollution category probabilities corresponding to the preset monitoring area from the multiple basic pollution category probabilities; According to the basic pollution partition identifiers of the designated number of pollution level target basic pollution category probabilities, the evaluation unit parameters in the to-be-removed partition evaluation sub-vector are removed to obtain the optimized partition evaluation sub-vector; The optimized evaluation vector is obtained according to the plurality of optimized partition evaluation sub-vectors.

6. The method according to claim 3, characterized in that The step of obtaining a water quality assessment result according to the optimized assessment vector and the water quality feature set includes: Obtaining target comprehensive water quality characteristics according to the optimized evaluation vector and the water quality characteristic set; Determine the pollution type of the target comprehensive water quality characteristics to obtain the pollution category probability; Conduct pollution zoning determination on the target comprehensive water quality characteristics to obtain pollution zoning identification; The water quality assessment result is obtained according to the pollution category probability and the pollution zone identification.

7. The method according to claim 6, characterized in that The target comprehensive water quality characteristics are obtained according to the optimized evaluation vector and the water quality characteristics set, including: Performing pollution feature interaction processing on the optimized evaluation vector to obtain a target evaluation vector; Performing water quality correlation analysis on the target evaluation vector and the water quality feature set to obtain the target comprehensive water quality feature; The step of obtaining a target comprehensive water quality feature according to the optimized evaluation vector and the water quality feature set further comprises: When it is determined that the current cycle is less than the preset cycle number, the pollution feature interaction processing is performed on the target evaluation vector of the previous cycle to obtain the target evaluation vector of the current cycle; Performing water quality correlation analysis on the current cycle target evaluation vector and the comprehensive water quality characteristics of the previous cycle to obtain the comprehensive water quality characteristics of the current cycle; When it is determined that the current cycle is equal to the preset number of cycles, the target comprehensive water quality characteristics are determined according to the comprehensive water quality characteristics of the current cycle.

8. The method according to claim 3, characterized in that Also includes: The basic assessment vector is subjected to pollution feature interactive processing to obtain the assessment vector, wherein the basic assessment vector includes a plurality of dynamically adjustable assessment unit parameters, and the dynamically adjustable assessment unit parameters are obtained through training of a historical water quality sample set and pollution level annotations corresponding to the historical water quality sample set.

9. A bioretention and purification device for collecting and treating rainwater at a port terminal, characterized in that: include: The purification module is used to collect rainwater from the port yard drainage ditch that has been initially filtered by the grille through a rainwater collection pipe; deeply purify the rainwater through a biological filter tank, and store the deeply purified rainwater in a target water collection tank through a water collection pipe; the biological filter tank includes a vegetation layer, a water separation layer, a microbial filler layer, a support layer, and a percolation layer; The evaluation module is used to evaluate the water quality of the target water collection pool at preset time intervals to obtain a water quality evaluation result; when the water quality evaluation result indicates that biological retention purification has passed, a recycled water reuse task is configured for the target water collection pool.

10. A readable storage medium, characterized in that: The readable storage medium includes a computer program, and when the computer program is executed, the computer device where the readable storage medium is located is controlled to execute the method according to any one of claims 1 to 8.

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