Industrial water pressure space diagnosis method based on multi-source data fusion

Abstract

The invention provides an industrial water pressure space diagnosis method based on multi-source data fusion. The method comprises the following steps: distributing water consumption, water quality demand and water pollutant emission data of each enterprise to POI point locations of each enterprise to obtain enterprise POI fusion information fused with multi-source data; dividing a space control unit in combination with a catchment boundary, and superposing the space control unit with enterprise POI fusion information to obtain a comprehensive space control unit; a grey water footprint model is improved by incorporating enterprise differentiated water quality demand parameters, a water resource pressure index giving consideration to enterprise differentiated water quality and water demand is constructed in combination with differentiated water demand parameters, the industrial water pressure of each comprehensive space control unit is quantified, and an industrial water pressure level spatial distribution diagram is drawn for diagnosis. The problem that in the prior art, enterprise POI distribution, enterprise differentiated water quality and water demand data are difficult to comprehensively consider to evaluate the industrial water pressure, and consequently the diagnosis result and the industrial water management and control demand are disjointed is solved.

Description

Technical Field

[0001] This invention relates to the field of industrial environmental management technology, and in particular to a spatial diagnostic method for industrial water pressure based on multi-source data fusion. Background Technology

[0002] Under the dual constraints of water scarcity and high-quality industrial development, accurate diagnosis of industrial water pressure is a core prerequisite for optimizing regional water resource allocation and formulating water management policies. Currently, industrial water pressure assessment technologies mostly focus on single-dimensional data applications. For example, some technologies rely solely on water volume monitoring data, measuring industrial water pressure by calculating indicators such as total water consumption and water efficiency, ignoring the impact of differentiated water demand and spatial distribution characteristics of enterprises on the water supply and demand pattern. Other technologies emphasize water quality monitoring data, using grey water footprints to assess the degree of water pollution. They typically reflect the level of water pollution by calculating the amount of water required to dilute pollutants discharged by enterprises to the required Class V water quality standard, failing to fully reflect the differentiated water quality needs of different enterprises and their spatial coupling relationship with enterprise layout.

[0003] Meanwhile, while Points of Interest (POI) data serves as a key carrier for characterizing the spatial distribution of industries, its application in diagnosing industrial water pressure remains significantly limited. Existing technologies often fail to effectively integrate information such as POI distribution and industry type with differentiated water quality and quantity demand data from enterprises. This results in assessment models that cannot accurately reflect the differentiated water quality and quantity demands of enterprises in different regions, as well as the driving effect of enterprise layout differences on water pressure. Consequently, existing industrial water pressure diagnostic results are difficult to match actual management needs, and cannot provide refined support for the formulation of differentiated water management strategies, thus hindering the efficient utilization of regional water resources and the sustainable development of industries. Summary of the Invention

[0004] The embodiments of the present invention provide a spatial diagnostic method for industrial water pressure based on multi-source data fusion, which aims to solve the problem that the existing technology is unable to comprehensively consider the distribution of enterprise POI, the differentiated water quality and water quantity demand data of enterprises to assess industrial water pressure, resulting in the diagnostic results being out of touch with the actual industrial water management needs.

[0005] To achieve the above objectives, this invention provides a spatial diagnostic method for industrial water pressure based on multi-source data fusion, comprising the following steps: Acquire multi-source industry data for the target area, including the POI locations and information of each enterprise, total water resources, water quality requirements of enterprises, water consumption and water pollutant discharge data of enterprises; The water consumption, water quality requirements and water pollutant discharge data of each enterprise are assigned to their respective POI locations to obtain enterprise POI fusion information of multi-source industrial data in the target area. By using an elevation model and based on the eight-axis method, the catchment boundary of the target area is divided to obtain a predetermined number of spatial control units for the target area. The enterprise POI fusion information is overlaid with the space control unit to obtain a comprehensive space control unit; By incorporating differentiated water quality demand parameters of enterprises to improve the grey water footprint model, and combining differentiated water quantity demand parameters, a water resource pressure index formula that takes into account the differentiated water quality and water quantity demands of enterprises is constructed to calculate the industrial water pressure of each integrated spatial control unit. The industrial water pressure is divided into a predetermined number of pressure levels according to a predetermined pressure threshold, and a spatial distribution map of the industrial water pressure levels is drawn as the diagnostic result of the industrial water pressure in the target area. The formula for the water resource pressure index is as follows: , , , , , , In the formula, To address the industrial water pressure while simultaneously accommodating the diverse water quality and quantity needs of businesses; To address the industrial water pressure based on the differentiated water demand of enterprises; To address the industrial water pressure based on the differentiated water quality needs of enterprises; For the first Water consumption per enterprise; This represents the total water consumption of all enterprises within the integrated space control unit; The amount of water resources available for use; For environmental flow requirements; Grey water footprint to account for differences in water quality requirements among enterprises; For the agricultural sector's grey water footprint; The leaching rate of nitrogen fertilizer refers to the mass proportion of pollutants entering natural water bodies relative to the total amount of fertilizer applied. The amount of freshwater used to treat this portion of pollutants is the grey water footprint of agriculture. The mass of nitrogen fertilizer applied to agriculture (ton / yr); For enterprises, under the circumstances of meeting the permissible water quality standards, the first Maximum acceptable concentration of pollutants (mg / m³) 3 ); The natural background concentration of pollutants in a water body under undisturbed conditions is usually assumed to be 0 (mg / m³). 3 ); Indicates the first industrial or service sector within the integrated space control unit. pollutants Departmental dilution water volume (m³) required for water quality of Class I water use 3 / yr); =1, 2, ..., According to data collection, water pollutants generally include chemical oxygen demand, ammonia nitrogen, total phosphorus, and total nitrogen. =1, 2, ..., 4, representing Class II and above water quality requirements, Class III water quality requirements, Class IV water quality requirements, and Class V water quality requirements, respectively; The number of enterprises within the integrated space control unit that meet the water quality requirements for Class m water use; It is the integrated space control unit. The first company The load of each pollutant (ton / yr).

[0006] Furthermore, the enterprise POI location and information include the enterprise's location, the type of industry to which the enterprise belongs, and / or its production scale.

[0007] Furthermore, it also includes: based on the national economic classification standards and the characteristics of enterprises' water quality needs, and with reference to national water quality standards, classifying enterprises' water quality needs into Class II and above water quality needs, Class III water quality needs, Class IV water quality needs, and / or Class V water quality needs.

[0008] Furthermore, the pressure threshold and the pressure level include: When the industrial water pressure is greater than or equal to a preset first pressure threshold, the pressure level is the preset first pressure level; When the industrial water pressure is less than a preset first pressure threshold and greater than or equal to a preset second pressure threshold, the pressure level is the preset second pressure level; When the industrial water pressure is less than a preset second pressure threshold and greater than or equal to a preset third pressure threshold, the pressure level is the preset third pressure level; When the industrial water pressure is less than a preset third pressure threshold and greater than or equal to a preset fourth pressure threshold, the pressure level is the preset fourth pressure level. When the industrial water pressure is less than a preset fourth pressure threshold, the pressure level is a preset fifth pressure level; The pressure thresholds, in descending order, are: first pressure threshold, second pressure threshold, third pressure threshold, and fourth pressure threshold. The pressure ratings, in descending order, are: first pressure rating, second pressure rating, third pressure rating, fourth pressure rating, and fifth pressure rating.

[0009] Further, the first pressure threshold is 3; the second pressure threshold is 1; the third pressure threshold is 0.4; and the fourth pressure threshold is 0.2. Furthermore, the spatial distribution map of industrial water pressure levels is drawn using GIS software, and the spatial distribution map is updated by collecting multi-source industrial data at specific time steps.

[0010] Furthermore, the spatial distribution map of industrial water pressure levels uses different colors to visualize and provide early warnings for the pressure levels of each integrated spatial control unit.

[0011] Furthermore, when the pressure level of a certain integrated spatial control unit is identified as being higher than a preset pressure level threshold, a pressure transmission path map of the spatial control unit to downstream sensitive targets is automatically generated based on the hydrological topology and river network data of the spatial control unit. The key control nodes and potential impact ranges on each transmission path are marked by the pressure transmission path map, and the cumulative pressure intensity on downstream sensitive targets is quantitatively assessed. Combining real-time hydrological data and a predetermined hydrodynamic-water quality model, the pollution migration process of pollutant emissions is simulated and an early warning is issued.

[0012] Furthermore, it also includes: predicting the spatial distribution of industrial water pressure in the target area under different scenarios by setting different control parameters and using a pre-trained machine learning model, and generating a comparison view; outputting a list of differentiated control measures for areas with different pressure levels based on the prediction results; the control parameters include enterprise access standards, pollution discharge limits and the proportion of water-saving technology transformation.

[0013] The above technical solution has the following technical effects: This invention acquires multi-source industrial data for a target area, including the locations and information of each enterprise's Point of Interest (POI), total water resources, water quality requirements, and pollutant discharge data. The total water resources, water quality requirements, and pollutant discharge data are allocated to each enterprise's POI to obtain integrated enterprise POI information from the multi-source industrial data of the target area. The catchment boundaries of the target area are delineated using an elevation model and an eight-axis method to obtain a predetermined number of spatial control units. The integrated enterprise POI information is overlaid with the spatial control units to obtain a comprehensive spatial control unit. The grey water footprint model is improved by incorporating differentiated water quality requirements from enterprises, and combined with differentiated water quantity requirements, a water resource pressure index that considers both differentiated water quality and quantity requirements of enterprises is constructed to quantify the industrial water pressure of each comprehensive spatial control unit. Based on predetermined pressure thresholds, the industrial water pressure is divided into a predetermined number of pressure levels, and a spatial distribution map of the industrial water pressure levels is drawn as the diagnostic result for the industrial water pressure in the target area. This invention solves the problem that existing technologies struggle to comprehensively consider enterprise POI distribution, differentiated water quality, and water quantity requirements to assess industrial water pressure, leading to a disconnect between diagnostic results and actual industrial water management needs. Attached Figure Description

[0014] Figure 1 This is a flowchart illustrating a spatial diagnostic method for industrial water pressure based on multi-source data fusion, according to an embodiment of the present invention. Detailed Implementation

[0015] To further illustrate the various embodiments, the present invention provides accompanying drawings. These drawings are part of the disclosure of the present invention, primarily used to illustrate the embodiments and to explain the operating principles of the embodiments in conjunction with the relevant descriptions in the specification. With reference to these drawings, those skilled in the art should be able to understand other possible implementations and the advantages of the present invention. Components in the drawings are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0016] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments.

[0017] Figure 1 This is a flowchart illustrating a spatial diagnostic method for industrial water pressure based on multi-source data fusion, according to an embodiment of the present invention. Figure 1 As shown, this invention provides a spatial diagnostic method for industrial water pressure based on multi-source data fusion, comprising the following steps: Acquire multi-source industry data for the target area, including the POI locations and information of each enterprise, total water resources, water quality requirements of enterprises, water consumption and water pollutant discharge data of enterprises; In one specific implementation, the enterprise's POI location and information include key basic information such as the enterprise's location, industry type, and production scale.

[0018] In one specific implementation, enterprise points of interest (POIs) are derived from the POI dataset of Gaode Maps (Amap). During factory production activities, wastewater and chemicals are typically discharged into nearby rivers, lakes, or oceans, leading to water quality deterioration. First, based on the national economic classification standards and the water quality requirements of enterprises, and strictly adhering to national water quality standards, enterprises are meticulously categorized into those using Class II or higher, Class III, Class IV, and Class V water quality. Then, using ArcGIS 10.8 kernel density analysis with a bandwidth of 5km, the kernel density of the factories is obtained. This data not only reflects the spatial distribution of factories but also their spatial clustering.

[0019] In one specific implementation, data such as the total water resources of the target area, water consumption of different industries, and water pollutant emissions are extracted from water resources bulletins, statistical yearbooks, etc.

[0020] The water consumption and water pollutant discharge data of each enterprise are assigned to their respective POI locations to obtain enterprise POI fusion information of multi-source industrial data in the target area. It is important to note that allocating water consumption and pollutant discharge data of each enterprise to their respective POI locations is not a simple data aggregation. Instead, it involves establishing multi-dimensional matching rules based on the enterprise's unified social credit code, discharge permit number, or name and address to achieve precise correlation and verification between attribute data and spatial locations. The merged POI is no longer merely a geographical label, but a spatialized data carrier carrying the key behavioral attributes of enterprises' water resource "intake-use-discharge". Each location is assigned specific water resource consumption intensity (e.g., annual water intake), water environment disturbance intensity (e.g., discharge of major pollutants such as chemical oxygen demand and ammonia nitrogen), and water quality requirements (e.g., the enterprise's maximum acceptable concentration of major pollutants such as chemical oxygen demand and ammonia nitrogen in the water body). This merged information lays a precise data foundation for subsequent pressure calculations within natural geographical units such as catchment areas, enabling industrial water pressure assessments to accurately reflect the spatially uneven distribution and specific sources of water pressure.

[0021] By using an elevation model and based on the eight-axis method, the catchment boundary of the target area is divided to obtain a predetermined number of spatial control units for the target area. In this embodiment, the digital elevation model provides high-precision topographic relief information, and the eight-direction rule, based on a water flow direction algorithm, simulates the natural confluence path of surface runoff, thereby scientifically defining the scope of each independent catchment area. The resulting spatial control units not only follow the natural laws of hydrological processes but also achieve a systematic deconstruction of the surface hydrological network of the target area. These units serve as the basic carriers for subsequent multi-source data fusion and pressure calculation, effectively supporting the accurate attribution and quantitative assessment of industrial water use, drainage, and other activities in hydrological space.

[0022] In one specific implementation, the digital elevation data used in the process comes from NASA. It represents ground elevation as an ordered numerical array, accurately and in detail expressing the characteristics of the Earth's surface topography. Slope data is calculated based on the digital elevation data using ArcGIS 10.8. Land cover data comes from the China Land Cover Dataset. This dataset provides nine land cover types, including cultivated land, forest, and impervious surfaces, with a spatial resolution of 30 meters from 1990 to 2024. Since land cover data for 2025 has not yet been generated, the 2024 land cover data is used instead. Using ArcGIS 10.8, a binary classification method is used to select three land cover types from this dataset: cultivated land, forest, and impervious surfaces. These three land cover types are set to 1, while other land cover types are set to 0.

[0023] By overlaying enterprise POI fusion information with spatial control units, a comprehensive spatial control unit is obtained. In one specific implementation, based on the enterprise POI fusion information, GIS spatial overlay analysis technology is used to overlay and associate it with spatial control units based on hydrological processes, ultimately generating a comprehensive spatial control unit carrying multi-dimensional attributes. Each comprehensive spatial control unit not only retains its inherent natural hydrological boundary characteristics, but also, through overlay analysis, is endowed with refined water resource behavior attributes of all enterprises within the unit.

[0024] By incorporating differentiated water quality demand parameters of enterprises to improve the grey water footprint model, and combining differentiated water quantity demand parameters, a water resource pressure index that takes into account the differentiated water quality and water quantity demands of enterprises is constructed to quantify the industrial water pressure of each integrated spatial control unit. Specifically, the industrial water pressure index for each unit is composed of two key dimensions: first, resource depletion pressure, reflecting the intensity of water use, measured by the ratio of actual industrial water intake to the available local water resources; and second, ecological stress pressure, characterizing the water pollution load, reflected by the ratio of the theoretical water volume required to dilute major pollutant emissions to the maximum acceptable concentration standard for each enterprise (i.e., the improved grey water footprint taking into account the differentiated water quality of enterprises) to the available water resources. This calculation framework solves the technical problem that water quality and quantity indicators in traditional assessments are difficult to reflect the differentiated water quantity and quality needs of enterprises, enabling each spatial unit to obtain a standardized pressure value that comprehensively considers the differentiated water quantity and quality needs of enterprises.

[0025] In one specific implementation, the formula for the water resource pressure index is as follows: , , , , , , In the formula, To balance the industrial water pressures caused by the differentiated water quality and quantity needs of enterprises; The industrial water pressure based on the differentiated water demand of enterprises is defined as the first... The ratio of water consumption to available water resources for each enterprise; The industrial water pressure based on the differentiated water quality needs of enterprises is defined as the first... The ratio of an enterprise's grey water footprint to available water resources based on its differentiated water quality needs; For the first Water consumption per enterprise; This represents the total water consumption of all enterprises within the integrated space control unit; The amount of water resources available for use; For environmental flow requirements; To account for the grey water footprint of enterprises with varying water quality requirements, the use of chemical fertilizers applied during crop growth and animal excrement from livestock farming are considered non-point source pollution. Therefore, a formula is used... Calculate the grey water footprint of the primary industry; the secondary and tertiary industries are typical point source pollutants, meaning pollutants are discharged from their original locations into natural water bodies, therefore, the grey water footprint is calculated. Calculate the grey water footprint of the secondary industry sub-sectors and the tertiary industry; since industrial sectors discharge multiple water pollutants, the grey water footprint of each sector should be determined by quantifying the grey water footprint of the most specific pollutant. Therefore, utilize... Determine the department's greywater footprint; For the agricultural sector's grey water footprint; The leaching rate of nitrogen fertilizer refers to the mass proportion of pollutants entering natural water bodies relative to the total amount of fertilizer applied. The amount of freshwater used to treat this portion of pollutants is the grey water footprint of agriculture. The mass of nitrogen fertilizer applied to agriculture (ton / yr); For enterprises, under the circumstances of meeting the permissible water quality standards, the first Maximum acceptable concentration of pollutants (mg / m³) 3 ); The natural background concentration of pollutants in a water body under undisturbed conditions is usually assumed to be 0 (mg / m³). 3 ); Indicates the first industrial or service sector within the integrated space control unit. pollutants Departmental dilution water volume (m³) required for water quality of Class I water use 3 / yr); =1, 2, ..., According to data collection, water pollutants generally include chemical oxygen demand, ammonia nitrogen, total phosphorus, and total nitrogen. =1, 2, ..., 4, representing Class II and above water quality requirements, Class III water quality requirements, Class IV water quality requirements, and Class V water quality requirements, respectively; The number of enterprises within a comprehensive spatial control unit that meet the same water quality requirements; It is the first in the integrated space control unit The first company The load of each pollutant (ton / yr).

[0026] Based on predetermined pressure thresholds, industrial water pressure is divided into a predetermined number of pressure levels, and a spatial distribution map of industrial water pressure levels is drawn as the diagnostic result of industrial water pressure in the target area.

[0027] In one specific implementation, the pressure threshold and pressure level include: When the industrial water pressure is greater than or equal to the preset first pressure threshold, the pressure level is the preset first pressure level, such as extreme water pressure. When the industrial water pressure is less than the preset first pressure threshold and greater than or equal to the preset second pressure threshold, the pressure level is the preset second pressure level, such as severe water pressure. When the industrial water pressure is less than the preset second pressure threshold but greater than or equal to the preset third pressure threshold, the pressure level is the preset third pressure level, such as medium water pressure. When the industrial water pressure is less than the preset third pressure threshold but greater than or equal to the preset fourth pressure threshold, the pressure level is the preset fourth pressure level, such as low water pressure. When the industrial water pressure is less than the preset fourth pressure threshold, the pressure level is the preset fifth pressure level, such as no water pressure. The pressure thresholds, in descending order, are: first pressure threshold, second pressure threshold, third pressure threshold, and fourth pressure threshold. The pressure ratings, in descending order, are: first pressure rating, second pressure rating, third pressure rating, fourth pressure rating, and fifth pressure rating.

[0028] In one specific implementation, the first pressure threshold is 3; the second pressure threshold is 1; the third pressure threshold is 0.4; and the fourth pressure threshold is 0.2. In one specific implementation, the spatial distribution map of industrial water pressure levels is drawn using GIS software, and the spatial distribution map is updated by collecting multi-source industrial data at a specific time step.

[0029] In one specific implementation, the spatial distribution map of industrial water pressure levels uses five different colors, such as red, orange, yellow, green, and blue, to visualize and provide early warnings of the pressure levels of each integrated spatial control unit.

[0030] In this embodiment, a Geographic Information System (GIS) platform is used to create and dynamically update a spatial distribution map of industrial water pressure levels. First, based on the quantified pressure values ​​of each spatial unit, color rendering is performed according to preset level thresholds to generate a map that intuitively reflects the spatial distribution characteristics of pressure. Furthermore, the system automatically collects and updates multi-source data at fixed time steps, such as annually. This data undergoes standardized fusion processing and pressure model recalculation, driving the GIS platform to automatically update the map's spatial attributes and visualization. This ensures that the diagnostic results can continuously track the impact of industrial layout adjustments, enterprise production fluctuations, and changes in water resource conditions, transforming the static spatial distribution map into a timely decision support tool. Through regular updates, management departments can grasp the evolution trend of pressure distribution, promptly identify emerging high-risk areas, and provide continuous spatial decision-making basis for water resource allocation, industrial access, and pollution control.

[0031] In one specific implementation, when a high-risk industrial cluster is identified, such as an area with a pressure level greater than the third pressure level, a pressure transmission path map of the high-risk unit to downstream sensitive targets, such as drinking water sources and ecological protection areas, is automatically generated based on the hydrological topology and river network data of the spatial control unit. This map dynamically marks the key control nodes and potential impact ranges on each transmission path and quantitatively assesses the cumulative pressure intensity on downstream sensitive targets. Finally, by combining real-time hydrological data with a predetermined hydrodynamic-water quality model, such as the MIKE model, the pollution migration process under high-risk emission scenarios is simulated and warned, providing spatial decision-making basis for upstream and downstream coordinated management and emergency response in the basin.

[0032] In one specific implementation, a multi-scenario simulation engine for industrial layout optimization and water resource regulation is also constructed. Managers set different regulation parameters, such as enterprise access standards, pollution discharge limits, and the proportion of water-saving technology transformation. Based on historical data and machine learning models such as random forest models, the spatial redistribution of industrial water pressure in the target area under each scenario is predicted, and a comparison view is generated. Based on the simulation results, a list of differentiated control measures for areas with different pressure levels is automatically output, such as double emission reduction in high-pressure areas and promoting water recycling in medium-pressure areas, forming a closed-loop decision support consisting of diagnosis, simulation, and regulation.

[0033] Although the invention has been specifically shown and described in conjunction with preferred embodiments, those skilled in the art should understand that various changes in form and detail may be made to the invention without departing from the spirit and scope of the invention as defined in the appended claims, all of which shall be within the scope of protection of the invention.

Claims

1. A spatial diagnostic method for industrial water pressure based on multi-source data fusion, characterized in that, Includes the following steps: Acquire multi-source industry data for the target area, including the POI locations and information of each enterprise, total water resources, water quality requirements of enterprises, water consumption and water pollutant discharge data of enterprises; The water consumption, water quality requirements and water pollutant discharge data of each enterprise are assigned to their respective POI locations to obtain enterprise POI fusion information of multi-source industrial data in the target area. By using an elevation model and based on the eight-axis method, the catchment boundary of the target area is divided to obtain a predetermined number of spatial control units for the target area. The enterprise POI fusion information is overlaid with the space control unit to obtain a comprehensive space control unit; By incorporating differentiated water quality demand parameters of enterprises to improve the grey water footprint model, and combining differentiated water quantity demand parameters, a water resource pressure index formula that takes into account the differentiated water quality and water quantity demands of enterprises is constructed to calculate the industrial water pressure of each integrated spatial control unit. The industrial water pressure is divided into a predetermined number of pressure levels according to a predetermined pressure threshold, and a spatial distribution map of the industrial water pressure levels is drawn as the diagnostic result of the industrial water pressure in the target area. The formula for the water resource pressure index, which takes into account the differentiated water quality and quantity needs of enterprises, is as follows: ， ， ， ， ， ， In the formula, To balance the industrial water pressures caused by the differentiated water quality and quantity needs of enterprises; To address the industrial water pressure based on the differentiated water demand of enterprises; To address the industrial water pressure based on the differentiated water quality needs of enterprises; For the first Water consumption per enterprise; This represents the total water consumption of all enterprises within the integrated space control unit; This refers to the amount of water resources available for use. For environmental flow requirements; Grey water footprint to account for differences in water quality requirements among enterprises; For the agricultural sector's grey water footprint; This refers to the leaching rate of nitrogen fertilizer; The quality of nitrogen fertilizer applied to agriculture; For enterprises, under the circumstances of meeting the permitted water quality standards, the first The maximum acceptable concentration of each pollutant; The natural background concentration of pollutants in a body of water under conditions of no human interference; Indicates the first industrial or service sector within the integrated control unit. pollutants The amount of dilution water required by departments with water quality requirements; =1, 2, ..., ; =1, 2, ..., 4, representing Class II and above water quality requirements, Class III water quality requirements, Class IV water quality requirements, and Class V water quality requirements, respectively; The number of enterprises within the integrated space control unit that meet the water quality requirements for Class m water use; It is the integrated space control unit. The first company The load of various pollutants.

2. The spatial diagnostic method for industrial water pressure based on multi-source data fusion according to claim 1, characterized in that, The enterprise POI locations and information include the enterprise's location, the type of industry the enterprise belongs to, and / or its production scale.

3. The spatial diagnostic method for industrial water pressure based on multi-source data fusion according to claim 1, characterized in that, Also includes: Based on the national economic classification standards and the characteristics of water quality demand of enterprises, and with reference to national water quality standards, the water quality demand of enterprises is classified into Class II and above, Class III, Class IV and / or Class V.

4. The spatial diagnostic method for industrial water pressure based on multi-source data fusion according to claim 1, characterized in that, The pressure threshold and the pressure level include: When the industrial water pressure is greater than or equal to a preset first pressure threshold, the pressure level is the preset first pressure level; When the industrial water pressure is less than a preset first pressure threshold and greater than or equal to a preset second pressure threshold, the pressure level is the preset second pressure level; When the industrial water pressure is less than a preset second pressure threshold and greater than or equal to a preset third pressure threshold, the pressure level is the preset third pressure level; When the industrial water pressure is less than a preset third pressure threshold and greater than or equal to a preset fourth pressure threshold, the pressure level is the preset fourth pressure level. When the industrial water pressure is less than a preset fourth pressure threshold, the pressure level is a preset fifth pressure level; The pressure thresholds, in descending order, are: first pressure threshold, second pressure threshold, third pressure threshold, and fourth pressure threshold. The pressure ratings, in descending order, are: first pressure rating, second pressure rating, third pressure rating, fourth pressure rating, and fifth pressure rating.

5. The spatial diagnostic method for industrial water pressure based on multi-source data fusion according to claim 4, characterized in that, The first pressure threshold is 3; the second pressure threshold is 1; the third pressure threshold is 0.4; and the fourth pressure threshold is 0.

2.

6. The spatial diagnostic method for industrial water pressure based on multi-source data fusion according to claim 1, characterized in that, The spatial distribution map of industrial water pressure levels is drawn using GIS software, and the spatial distribution map is updated by collecting multi-source industrial data at specific time steps.

7. The spatial diagnostic method for industrial water pressure based on multi-source data fusion according to claim 1, characterized in that, The spatial distribution map of industrial water pressure levels uses different colors to visualize and provide early warnings of the pressure levels of each integrated spatial control unit.

8. The spatial diagnostic method for industrial water pressure based on multi-source data fusion according to claim 1, characterized in that, When the pressure level of a certain integrated spatial control unit is identified as being higher than a preset pressure level threshold, a pressure transmission path map of the spatial control unit to downstream sensitive targets is automatically generated based on the hydrological topology and river network data of the spatial control unit. The key control nodes and potential impact ranges on each transmission path are marked by the pressure transmission path map, and the cumulative pressure intensity on downstream sensitive targets is quantitatively assessed. Combining real-time hydrological data and a predetermined hydrodynamic-water quality model, the pollution migration process of pollutant emissions is simulated and an early warning is issued.

9. The spatial diagnostic method for industrial water pressure based on multi-source data fusion according to claim 1, characterized in that, Also includes: By setting scenarios with different control parameters, the spatial distribution of industrial water pressure in the target area under each scenario is predicted by a pre-trained machine learning model, and a comparison view is generated. Based on the prediction results, a list of differentiated control measures for areas with different pressure levels is output. The control parameters include enterprise access standards, pollution discharge limits, and the proportion of water-saving technology transformation.

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