Water ecological environment problem diagnosis method and device based on drainage basin space tracking and city space refinement, equipment and storage medium

Abstract

The invention provides a water ecological environment problem diagnosis method and device based on drainage basin space tracking and city space refinement, equipment and a storage medium, and belongs to the technical field of water ecological environment protection and water quality safety, and the method comprises the steps: obtaining target region drainage basin catchment unit data based on a resistance factor; performing spatial self-correlation statistical analysis on the specific pollutant concentration of the catchment unit of the drainage basin to obtain a water environment problem outburst drainage basin; refining the drainage basin catchment units to obtain city catchment unit data; constructing a water ecological environment problem evaluation index system, and determining key city catchment unit data; and generating a water ecological environment problem data set according to the determined key city water catchment units and the corresponding water ecological environment problem indexes. According to the method, the influence of ground catchment resistance is fully considered when the catchment units of the drainage basin are divided, and the water ecological environment problem is diagnosed from the prefecture scale, so that the refined management of the water ecological environment problem is more targeted.

Description

Technical Field

[0001] The present invention relates to the field of water ecological environment protection and water quality safety technology, and in particular to a method and device, equipment and storage medium for diagnosing water ecological environment problems based on watershed spatial tracking and urban spatial refinement. Background Art

[0002] The protection and management of water ecological environment is crucial to the sustainable use of water resources. With the development of society, the demand for refined management of water ecological environment is gradually increasing. Analyzing water ecological environment problems only from the perspective of the entire river basin and province can no longer meet the requirements of "precise" management. At present, the refined management of water ecological environment and the division of spatial units are mostly concentrated on the division method of natural watershed range and its related environmental zoning integration with DEM data as the core. For example, CN115757367A discloses a method for refined management and control of water ecological environment in small watersheds, which investigates and obtains water ecological environment status data information of the target watershed, and the water ecological environment status data information includes DEM layer information; the target watershed is divided into spatial density differentiation according to the water ecological environment status data information of the target watershed to obtain multiple watershed units; CN117236603A discloses a water ecological environment management method that can realize the connection between administrative regions and watersheds, which obtains watershed hydrological analysis data of the target area based on the digital elevation model (DEM), uses hydrological analysis tools, and divides hydrological units in combination with the three-level water resources zoning data of the Ministry of Water Resources; based on the hydrological units, the watershed units are identified through watershed analysis by superimposing control sections, water system maps, pollution source data, and land use data; and the water ecological environment control units are generated by superimposing the watershed units with administrative divisions and administrative residence data. The above method does not take into account the influence of watershed resistance when dividing the watershed units. It also lacks a method for diagnosing water ecological environmental problems at the municipal scale. As a key level for promoting the continuous improvement of the water ecological environment in the river basin and implementing relevant governance measures, the municipal scale plays an important role in fundamentally solving the prominent water ecological environmental problems in the river basin. Summary of the invention

[0003] In response to the above problems, the present invention provides a method and device, equipment and storage medium for diagnosing water ecological environment problems based on watershed spatial tracking and urban spatial refinement.

[0004] The present invention provides a method for diagnosing water ecological environment problems based on watershed spatial tracking and city-wide spatial refinement, the method comprising: Acquire watershed unit data of a target area basin based on a resistance factor, wherein the resistance factor includes at least one of elevation, slope, aspect, undulation, and roughness; Conduct spatial autocorrelation statistical analysis on the concentration of characteristic pollutants in the catchment units of the target area to identify and obtain the watersheds with prominent water environment problems; Based on the obtained watershed with prominent water environment problems, the watershed catchment unit is refined with prefecture-level cities as basic units to obtain prefecture-level city catchment unit data; Constructing an evaluation index system for water ecological environment problems, and determining key prefecture-level city water catchment unit data from the prefecture-level city water catchment unit data based on the constructed water ecological environment problem index system; A water ecological environment problem data set is generated based on the determined key prefecture-level city water catchment units and the water ecological environment problem indicators corresponding to the key prefecture-level city water catchment units.

[0005] As a further improvement of the present invention, the acquisition of watershed unit data of the target area based on the resistance factor includes: Identify and generalize water systems; Determine the control section, and based on the water system generalization results, calculate the watershed catchment range corresponding to the section through the minimum path resistance value; Based on the geographic space boundary fitting technology, the administrative responsibility boundary and the watershed catchment range are coupled to obtain the watershed catchment unit of the target area; Among them, the control section is a national control section.

[0006] As a further improvement of the present invention, the identifying and generalizing water systems includes: Collection of vector and raster data of target area; DEM data preprocessing; DEM extraction of river network; River network and water system verification.

[0007] As a further improvement of the present invention, the control section is determined based on the water system generalization result, and the watershed catchment range corresponding to the section is calculated by the minimum path resistance value, including: Divide the target area into grids, perform weight analysis on the resistance factors using the analytic hierarchy process according to different terrains including plains, hills and mountains, obtain the weight value of each resistance factor of the corresponding terrain, and obtain the resistance coefficient for each spatial grid through weighted calculation; Establish a minimum resistance cumulative consumption distance model and calculate the plastic flow direction and path of the fluid particles in the space based on the resistance coefficient of each spatial grid, so as to obtain the minimum cost path from the source to the end; Based on the minimum cost path, the watershed catchment area corresponding to the section is obtained.

[0008] As a further improvement of the present invention, the minimum resistance cumulative consumption distance model is:

[0009] Where D ijis the spatial distance from source unit i to sink unit j; R i is the resistance coefficient in the transition process from source unit i to sink unit j; R i Depending on the value of i, the path from unit i to unit j produces different resistance values. When i is determined, calculating MCR requires selecting the path with the smallest resistance value in the spatial distance. This path conforms to the law of liquid flow and is the easiest path for runoff diffusion.

[0010] As a further improvement of the present invention, spatial autocorrelation statistical analysis is performed on the concentrations of characteristic pollutants in the watershed units of the target area, and watersheds with prominent water environment problems are identified and obtained, including spatial correlation analysis of characteristic pollutants in the watershed units of the target area based on the local Moran's index, wherein the characteristic pollutants include chemical oxygen demand, ammonia nitrogen and total phosphorus.

[0011] As a further improvement of the present invention, the formula of the local Moran index is:

[0012] In the formula, is the local Moran index, and Represent the attribute values ​​of units i and j respectively, is the mean of all unit attribute values, is the variance, Represents the spatial weight matrix, which is used to quantify the strength of the spatial relationship between i and j.

[0013] As a further improvement of the present invention, the step of constructing an evaluation index system for water ecological environment problems, and determining key prefecture-level city water catchment unit data from the prefecture-level city water catchment unit data based on the constructed water ecological environment problem index system comprises: Constructing the evaluation index system of the water ecological environment problems; The prefecture-level city water catchment units with water ecological environment problems are identified as the key prefecture-level city water catchment units.

[0014] On the other hand, the present invention also provides a device, including a watershed catchment unit data acquisition module, a watershed identification module with prominent water environment problems, a prefecture-level city catchment unit data acquisition module, a key prefecture-level city catchment unit data determination module, and a water ecological environment problem data set generation module; Among them, the watershed catchment unit data acquisition module is used to obtain the watershed catchment unit data of the target area based on the resistance factor; The module for identifying watersheds with prominent water environment problems conducts spatial autocorrelation statistical analysis on the concentration of characteristic pollutants in the catchment units of the target area to identify and obtain watersheds with prominent water environment problems; A prefecture-level city water catchment unit data acquisition module is used to refine the water catchment unit of the watershed based on the prominent watershed of the water environment problem obtained, taking the prefecture-level city as the basic unit, and obtain the prefecture-level city water catchment unit data; A key prefecture-level city water catchment unit data determination module is used to construct a water ecological environment problem evaluation index system, and determine the key prefecture-level city water catchment unit data from the prefecture-level city water catchment unit data based on the constructed water ecological environment problem index system; The water ecological environment problem data set generation module is used to generate a water ecological environment problem data set based on the determined water catchment unit data of the key cities and the water ecological environment problem indicators corresponding to the water catchment units of the key cities.

[0015] On the other hand, the present invention further provides a device, comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0016] On the other hand, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0017] The present invention provides a method and device, equipment and storage medium for diagnosing water ecological environment problems based on watershed spatial tracking and municipal spatial refinement. First, watershed-scale spatial unit division based on resistance factors is performed to obtain watershed catchment units. Then, spatial autocorrelation analysis is used to focus on spatial areas with water ecological environment problems. Spatial refinement of water ecological environment problems at the prefecture-level is performed on the spatial areas with water ecological environment problems to obtain prefecture-level catchment units. Finally, a water ecological environment problem evaluation index system is constructed to perform spatial diagnosis of water ecological environment problems at the prefecture-level, determine key prefecture-level catchment units with water ecological environment problems, and generate water ecological environment problem data sets for key prefecture-level catchment units. When dividing watershed catchment units, the influence of ground catchment resistance is fully considered, and water ecological environment problems are diagnosed at the prefecture-level, realizing the diagnosis of water ecological environment problems from the watershed focus area and then focusing on the prefecture-level, making the refined management of water ecological environment problems more targeted. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of a method for diagnosing water ecological environment problems based on watershed spatial tracking and urban spatial refinement according to an embodiment of the present invention.

[0019] Figure 2 It is a flow chart of obtaining water catchment units in a water ecological environment problem diagnosis method based on watershed spatial tracking and urban spatial refinement according to an embodiment of the present invention.

[0020] Figure 3Schematic diagram of the distribution of different terrains in the Yangtze River Basin according to an embodiment of the present invention.

[0021] Figure 4 It is a schematic diagram of the division results of the Yangtze River Basin water catchment units according to an embodiment of the present invention.

[0022] Figure 5 It is a schematic diagram of the spatial autocorrelation distribution of chemical oxygen demand, ammonia nitrogen and total phosphorus concentrations in the Yangtze River Basin catchment unit according to an embodiment of the present invention.

[0023] Figure 6 This is a distribution map of water catchment units in a certain city in the Yangtze River Basin according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The following is combined with specific embodiments and appendix Figure 1-6 The invention is described in detail so that those skilled in the art can more fully understand the purpose, features and effects of the invention.

[0025] Unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as commonly understood by those skilled in the art to which the present invention belongs. When the definition of a term in the present invention conflicts with the meaning commonly understood by those skilled in the art to which the present invention belongs, the definition described in the present invention shall prevail.

[0026] The present invention improves the pertinence of water ecological environment problem diagnosis by providing a water ecological environment problem diagnosis method and device, equipment and storage medium based on watershed spatial tracking and city-wide spatial refinement.

[0027] Embodiment 1 As a specific embodiment of the present invention, this embodiment provides a water ecological environment problem diagnosis method based on watershed spatial tracking and city spatial refinement, referring to Figure 1 , the specific steps are as follows: S100, obtaining watershed unit data of the target area based on the resistance factor; S200, performing spatial autocorrelation statistical analysis on the concentration of characteristic pollutants in the catchment units of the target area to identify and obtain the watersheds with prominent water environment problems; S300, based on the obtained watershed with prominent water environment problems, the watershed catchment unit is refined with prefecture-level cities as basic units to obtain prefecture-level city catchment unit data; S400, constructing a water ecological environment problem evaluation index system, and determining key prefecture-level city water catchment unit data from the prefecture-level city water catchment unit data based on the constructed water ecological environment problem index system; S500. Generate a water ecological environment problem data set based on the determined water catchment unit data of the key cities and the water ecological environment problem indicators corresponding to the water catchment units of the key cities.

[0028] The water ecological environment problem diagnosis method based on watershed spatial tracking and municipal spatial refinement in this embodiment first performs watershed-scale spatial unit division based on resistance factors to obtain watershed catchment units, then focuses on spatial areas with water ecological environment problems based on spatial autocorrelation analysis, and performs spatial refinement of water ecological environment problems at the prefecture-level in the spatial areas with water ecological environment problems to obtain prefecture-level catchment units, finally, spatially diagnoses water ecological environment problems at the prefecture-level through the constructed water ecological environment problem evaluation index system, determines key prefecture-level catchment units with water ecological environment problems, and generates a water ecological environment problem data set for key prefecture-level catchment units.

[0029] Specifically, in S100, refer to Figure 2 , the acquisition of watershed unit data of the target area based on the resistance factor includes: S101. Identify and generalize water systems With the help of GIS tools, the natural characteristics of the basin and actual needs are comprehensively considered, and the natural water system (rivers, lakes and reservoirs) is generalized into an applicable water system. The spatial expression is a number of intersecting straight lines or curves, mainly in the form of dendrites or networks. The endowment information includes the main stream, the main first-level tributaries and second-level tributaries, and the tributaries where the main pollution sources are located, including: Large-scale vector (river systems, administrative divisions, etc.) and high-resolution raster (DEM, remote sensing images, etc.) data collection; Digital elevation model (DEM) data preprocessing; DEM extraction of river network; River network and water system verification.

[0030] In the identification and generalization of water systems, it is carried out according to the principle that each sub-basin can only have one main river, that is, one flow path, and the flow direction of all rivers in the sub-basin should point to the main river, that is, to the flow path.

[0031] S102. Determine the catchment area of ​​the corresponding watershed The control sections are selected from the existing water quality monitoring sections, wherein the control sections are national control sections, which refer to the water quality control sections that have been given by the state and can be regularly monitored. Preferably, the control sections are selected by judging the representativeness, sensitivity and importance of the water quality of each control section, wherein the control sections can be set densely for heavily polluted areas, and the number of control sections can be appropriately reduced for areas with little human activities and no major pollution sources affecting water quality.

[0032] Furthermore, taking the screened control sections as nodes, based on the water system generalization results, the watershed catchment range corresponding to the section is calculated by the minimum path resistance value.

[0033] Specifically, they include: S1021. Divide the study area into grids, and use the Analytic Hierarchy Process (AHP) to perform weight analysis on resistance factors including elevation, slope, aspect, undulation, and roughness according to different terrains such as plains, hills, and mountains, and obtain the weight value of each resistance factor of the corresponding terrain, and obtain the resistance coefficient R for each spatial grid through weighted calculation. For example, in one example, the resistance factor may include five influencing factors: elevation, slope, aspect, undulation, and roughness, and the weight values ​​of the five influencing factors are different for different terrains such as plains, hills, and mountains; S1022. Establish the Minimum Cumulative Resistance (MCR) model to calculate the plastic flow direction and path of fluid particles in space, and obtain the minimum cost path from the source to the end:

[0034] Where D ij is the spatial distance from source unit i to sink unit j; R i is the resistance coefficient in the transition process from source unit i to sink unit j; R i Determined by the value of i, the path from i to j unit produces different resistance values. When i is determined, the calculation of MCR requires selecting the path with the smallest resistance value in the spatial distance. This path conforms to the law of liquid flow and is the easiest path for runoff diffusion.

[0035] Under the grid module of GIS software, the MCR model can determine the minimum cost path (the path with the smallest resistance value) between the "source" and the "target" according to the flow law of surface runoff, that is, the easiest path for surface runoff to diffuse in the region, and construct the surface runoff path and network structure, thereby obtaining the watershed catchment range corresponding to each section.

[0036] S103. Obtaining watershed unit data Taking the control section (national control) as the node and maintaining the integrity of the administrative boundary of the township as the constraint condition, the administrative districts involved in the watershed between the control nodes are combined to form the land area of ​​the watershed catchment unit. If there are multiple watershed destinations in an administrative district, it is necessary to determine its dominant destination in combination with the minimum cost path and assign it to a watershed catchment unit in its entirety; for administrative districts that are subject to greater human interference and involve sewage interception and diversion, the watershed catchment unit to which it belongs should be determined based on the actual drainage destination rather than the terrain.

[0037] In S100, based on the identification and generalization of water systems, the control section (national control) is used as a node, and the minimum resistance cumulative cost distance model is used to calculate the minimum path resistance value of each source unit (any unit except the sink unit) and sink unit (the unit where the national control section is located) in the spatial grid, and the catchment range of the river basin corresponding to each section is obtained; then based on the geographic space boundary fitting technology, on the basis of fully considering the natural catchment and sewage discharge characteristics of the river basin, the catchment unit division of the river basin is carried out by coupling the administrative responsibility boundary and the catchment range of the river basin with the minimum cost path. The division process must ensure the integrity of the administrative division and achieve full coverage of the river basin.

[0038] Specifically, in S200, spatial autocorrelation statistical analysis is performed on the characteristic pollutant concentrations of the catchment units in the target area to identify and obtain the prominent water environment problem watersheds, including: S201. Perform spatial correlation analysis on characteristic pollutants of watershed units in the target area based on the Local Moran's I, where the characteristic pollutants may be chemical oxygen demand, ammonia nitrogen and total phosphorus; S202. According to the results of spatial correlation analysis of characteristic pollutants in the catchment units of the target area, accurately identify and obtain areas with prominent water environment problems. The local Moran's index is a method for identifying where agglomeration phenomena and outliers occur in space, and can be used to characterize the degree of aggregation of water ecological environmental problems in different regions.

[0039] Furthermore, the formula of the local Moran index is:

[0040] In the formula, is the local Moran index, and Represent the attribute values ​​of units i and j respectively, is the mean of all unit attribute values, is the variance, Represents the spatial weight matrix, which is used to quantify the strength of the spatial relationship between i and j.

[0041] The value of the local Moran index falls within the interval [-1, 1]. A positive value indicates that the location has similar attribute values ​​to other locations in its neighborhood, forming a "high-high" or "low-low" spatial clustering pattern, while a negative value means that the location has opposite attribute values ​​to the locations in its neighborhood, presenting a "high-low" or "low-high" distribution. A value close to 0 indicates that there is no significant spatial autocorrelation between the location and the neighborhood, that is, the distribution of attribute values ​​is random.

[0042] By using the local Moran index to perform spatial autocorrelation statistics on the concentrations of characteristic pollutants in the watershed units of the target area, and conducting spatial clustering analysis on the concentrations of major pollutants in the watershed units of the target area, we can accurately identify watersheds with prominent water environment problems and improve the targeted nature of the next step of refining the watershed units in prefectures and cities.

[0043] Specifically, in S300, based on the obtained prominent watershed with water environment problems, the watershed catchment unit is refined with prefecture-level cities as basic units, and the prefecture-level city catchment unit data is obtained, including: Taking prefecture-level cities as the basic units, using national and local water quality monitoring sections (including national control sections, provincial control sections, municipal control sections, and county control sections), and following the method of obtaining watershed catchment unit data in S100, the watersheds with prominent water environment problems obtained in S200 are refined to form prefecture-level city catchment units.

[0044] In S300, refining the watershed catchment unit requires more detailed water system, pollution source distribution and water quality data, and the administrative divisions need to be further refined from township administrative divisions to village-level administrative divisions.

[0045] Specifically, in S400, the step of constructing an evaluation index system for water ecological environment problems, and determining key prefecture-level city water catchment unit data from the prefecture-level city water catchment unit data based on the constructed water ecological environment problem index system includes: S401. Construct an evaluation index system for water ecological environment issues In this embodiment, the evaluation index system includes three primary indicators, namely water environment, water resources, and water ecology, and 12 secondary indicators, as shown in Table 1.

[0046] Table 1 Evaluation index system of water ecological environment problems

[0047] In Table 1, the first-level water environment index includes five second-level indicators, namely: 1. The water quality of the section has deteriorated significantly: the relevant indicators of the sections under county control and above (national control, provincial control, municipal control, and county control) have shown a deteriorating trend year-on-year and month-on-month. The deteriorating trend means that the water quality category of the section has declined or the concentration of the main pollutants has increased by 20% or more; 2. High intensity of non-point source pollution: the ratio of the concentration of the primary pollutant after obvious rainfall runoff is formed in the upstream catchment area of ​​a section within 24 hours to the annual average concentration value of the index in the section in the past three years is greater than 2, among which the primary pollutant is determined by analyzing the water quality data of the section in the past three years and evaluating the water quality category of the section with the single factor evaluation method of the "Surface Water Environmental Quality Standard" (GB3838); 3. Existence of Class V controlled sections: There are Class V controlled sections in county-controlled sections and above (national-controlled, provincial-controlled, municipal-controlled, and county-controlled), which are determined by the monthly cumulative average; 4. The water quality of drinking water sources exceeds the standard: There are water quality exceeding the standard at centralized drinking water sources at the county level and above; 5. Existence of black and smelly water bodies: There are black and smelly water bodies in the city during the assessment year.

[0048] The first-level water resource index includes two second-level indicators, namely: 1. The rivers are dry (seasonal rivers are not considered): According to relevant monitoring data, the main rivers in the city are dry; 2. High intensity of water resource development and utilization: Compared with cities in the same river basin and at the same level of economic development, this city has a higher intensity of water resource development and utilization.

[0049] The first-level water ecological index includes five second-level indicators, namely: 1. Degradation of water conservation areas: According to the comparison of relevant monitoring data, the vegetation coverage area of ​​water conservation areas of major urban water bodies has decreased significantly year-on-year. For cities that have not demarcated water conservation areas, this indicator is not considered for the time being; 2. High risk of algal bloom outbreaks in lakes and reservoirs: According to lake and reservoir monitoring data, the risk of algal bloom outbreaks exceeds the yellow warning threshold; 3. Low natural shoreline ratio of rivers and lakes: refers to the ratio of the length of natural undeveloped shoreline or shoreline that has basically achieved its ecological function through ecological restoration to the total length of the shoreline, which is less than 50%; 4. Poor connectivity of river and lake systems: Compared with historical data, this usually refers to the 5-10 years before the assessment year, when there are many dams and locks per unit river length, among which dams and locks with effective ecological protection measures may not be included; 5. Decline in biodiversity: By evaluating the biodiversity index of the urban area, it is found that compared with the historical status, usually referring to the 5-10 years before the assessment year, the urban area biodiversity index (BI) has decreased by 1 or more levels. The calculation method of the regional biodiversity index refers to the "Regional Biodiversity Evaluation Standard" (HJ 623).

[0050] This embodiment constructs an evaluation index system for water ecological environment problems at the prefecture-level from three dimensions: water environment, water resources, and water ecology. The evaluation is comprehensive and highly integrated, thereby achieving an effective evaluation of water ecological environment problems at the prefecture-level.

[0051] S402. Identify the water catchment units in cities and prefectures with water ecological environment problems as key water catchment units in cities and prefectures.

[0052] Specifically, in S500, generating a water ecological environment problem data set according to the determined key prefecture-level city water catchment unit data and the water ecological environment problem indicators corresponding to the key prefecture-level city water catchment units includes: S501, determining the water ecological environment problem index corresponding to each key prefecture-level city water catchment unit obtained in S400, wherein each key prefecture-level city water catchment unit includes at least one water ecological environment problem index; S502. Combine all the water catchment units in key cities and their corresponding water ecological environment problem indicators to generate a water ecological environment problem data set.

[0053] Embodiment 2 As a specific embodiment of the present invention, this embodiment provides a method for diagnosing water ecological environment problems based on basin spatial tracking and city spatial refinement. Taking the Yangtze River Basin as an example, the diagnosis of water ecological environment problems is performed. The specific steps are as follows: S100, obtain the watershed unit data of the target area based on the resistance factor The Analytic Hierarchy Process (AHP) was used to analyze the weights of the influencing factors in different terrain conditions, including elevation, slope, slope aspect, undulation, and roughness, in the Yangtze River Basin. Figure 3 As shown in Table 2, the weights of resistance factors for surface runoff confluence under different terrain conditions of plains, hills and mountains in the Yangtze River Basin are obtained.

[0054] Table 2 AHP Yangtze River Basin resistance factor weight distribution table

[0055] In the early stage, the Yangtze River Basin was divided into 628 catchment units. Later, after further refinement and optimization of water quality monitoring sections, the Yangtze River Basin was divided into 1252 catchment units. Figure 4 shown.

[0056] S200, perform spatial autocorrelation statistical analysis on the concentration of characteristic pollutants in the catchment units of the target area, and identify and obtain the watersheds with prominent water environment problems Based on the spatial correlation analysis of the local Moran index, the annual average concentrations of the main pollutants chemical oxygen demand, ammonia nitrogen and total phosphorus in the water quality sections of the Yangtze River Basin in 2023 were spatially clustered to identify areas with prominent water environment problems. The results are as follows: Figure 5 shown.

[0057] Judging from the results of spatial autocorrelation analysis, chemical oxygen demand, ammonia nitrogen and total phosphorus all showed obvious spatial clustering phenomena. The "high-high clustering" areas of the three major pollutions were mainly distributed in the Yangtze River Delta, Jianghan Plain, Sichuan Basin, Nanyang Basin, Dianchi Lake Basin, Chaohu Lake Basin and other regions. From the perspective of provinces, pollution clustering areas were mainly distributed in the eastern part of Hubei Province, southern Jiangsu Province, eastern Sichuan Province, central Anhui Province, and most areas of Shanghai.

[0058] S300, based on the obtained watershed with prominent water environment problems, the watershed catchment unit is refined with the prefecture-level city as the basic unit to obtain the prefecture-level city catchment unit data For the Yangtze River Basin with prominent water environment problems, a certain prefecture-level administrative region was used as an example for analysis. A total of 50 water quality monitoring sections were set up in the prefecture-level city, of which 16 were controlled by the state, 18 by the province, and 16 by the city. Through refinement, the prefecture-level city was divided into 44 prefecture-level water catchment units, as follows: Figure 6 shown.

[0059] S400: construct an evaluation index system for water ecological environment problems, and determine key prefecture-level city water catchment unit data from the prefecture-level city water catchment unit data based on the constructed water ecological environment problem index system. For each water catchment unit of the prefecture-level city, a comparison is made based on the water ecological environment problem indicators in the constructed water ecological environment problem indicator system, and the key water catchment units of the prefecture-level city are obtained from all the water catchment units of the prefecture-level city. For the 44 prefecture-level water catchment units divided according to S300, the 12 secondary indicators in the water ecological environment problem index system were analyzed. All prefecture-level water catchment units with water ecological environment problems were regarded as key prefecture-level water catchment units, and the prefecture-level water catchment units without water ecological environment problem indicators were excluded. A total of 16 key prefecture-level water catchment units were screened out, as shown in Table 3. Among them, the number of key prefecture-level water catchment units corresponding to one secondary water ecological problem environmental indicator varied. For example, the indicator of poor connectivity of river and lake water systems existed in 6 key prefecture-level water catchment units, the indicator of river dry-up (seasonal rivers were not considered) existed in 4 key prefecture-level water catchment units, and the indicators of excessive water quality of drinking water sources, black and smelly water bodies, high intensity of water resources development and utilization, and low natural shoreline rate of rivers and lakes did not exist in all prefecture-level water catchment units.

[0060] Table 3 Number of water catchment units in cities corresponding to the water ecological environment problem evaluation index system

[0061] S500: Generate a water ecological environment problem data set based on the determined water catchment unit data of the key cities and the water ecological environment problem indicators corresponding to the water catchment units of the key cities Based on the 16 key water catchment units in the prefecture-level city and their corresponding water ecological environment problem indicators, a water ecological environment problem dataset was generated to guide the refined management of the water ecological environment in the prefecture-level city. The results are shown in Table 4.

[0062] Table 4 Dataset of water ecological environment problems in water catchment units in key cities

[0063] In this embodiment, 16 key prefecture-level city water catchment units of a certain prefecture-level city are determined according to S400, and a water ecological environment problem data set of key prefecture-level city water catchment units is generated. The water ecological environment problems corresponding to each key prefecture-level city water catchment unit are given. Each key prefecture-level city water catchment unit corresponds to at least one water ecological environment problem. Among them, the prefecture-level city water catchment unit No. 14 corresponds to three water ecological environment problem indicators, namely, poor connectivity of river and lake systems, decreased biodiversity, and degradation of water source conservation areas. It is a key prefecture-level city water catchment unit that should be paid special attention to, followed by the prefecture-level city water catchment unit No. 2, the prefecture-level city water catchment unit No. 16, and the prefecture-level city water catchment unit No. 20.

[0064] Embodiment 3 As a specific embodiment of the present invention, this embodiment provides a water ecological environment problem diagnosis device based on watershed spatial tracking and municipal spatial refinement, including: a watershed watershed unit data acquisition module, a watershed identification module with prominent water environment problems, a prefecture-level city watershed unit data acquisition module, a key prefecture-level city watershed unit data determination module and a water ecological environment problem data set generation module.

[0065] Among them, the watershed catchment unit data acquisition module is used to obtain the watershed catchment unit data of the target area based on the resistance factor; The module for identifying watersheds with prominent water environment problems conducts spatial autocorrelation statistical analysis on the concentration of characteristic pollutants in the catchment units of the target area to identify and obtain watersheds with prominent water environment problems; A prefecture-level city water catchment unit data acquisition module is used to refine the water catchment unit of the watershed based on the prominent watershed of the water environment problem obtained, taking the prefecture-level city as the basic unit, and obtain the prefecture-level city water catchment unit data; A key prefecture-level city water catchment unit data determination module is used to construct a water ecological environment problem evaluation index system, and determine the key prefecture-level city water catchment unit data from the prefecture-level city water catchment unit data based on the constructed water ecological environment problem index system; The water ecological environment problem data set generation module is used to generate a water ecological environment problem data set based on the determined water catchment unit data of the key cities and the water ecological environment problem indicators corresponding to the water catchment units of the key cities.

[0066] Embodiment 4 As a specific embodiment of the present invention, this embodiment provides a device, including a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to implement the steps of the method described in Embodiment 1.

[0067] Embodiment 5 As a specific embodiment of the present invention, this embodiment provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is used to implement the steps of the method described in Embodiment 1.

[0068] The water ecological environment problem diagnosis method, device, equipment and storage medium based on watershed spatial tracking and municipal spatial refinement of the present invention first divides the target area into watershed catchment units, and then focuses on key watershed catchment units with more prominent water environment problems through spatial autocorrelation statistical methods, and further refines the relevant watershed catchment units into municipal catchment units at the municipal level, comprehensively analyzes and judges water ecological environment problems at the municipal scale from the three dimensions of "water environment, water resources, and water ecology", so as to achieve the focus on water environment problems at the watershed scale and the diagnosis of water ecological environment problems at the municipal scale.

[0069] The above description is only a preferred embodiment of the present invention and does not constitute any other form of limitation to the present invention. Any modification or equivalent change made based on the technical essence of the present invention still falls within the scope of protection required by the present invention.

Claims

1. A method for diagnosing water ecological environment problems based on basin spatial tracking and city spatial refinement, It is characterized in that The method comprises: Acquire watershed unit data of a target area based on a resistance factor, wherein the resistance factor includes at least one of elevation, slope, aspect, undulation, and roughness; Conduct spatial autocorrelation statistical analysis on the concentration of characteristic pollutants in the catchment units of the target area to identify and obtain the watersheds with prominent water environment problems; Based on the obtained watershed with prominent water environment problems, the watershed catchment unit is refined with prefecture-level cities as basic units to obtain prefecture-level city catchment unit data; Constructing an evaluation index system for water ecological environment problems, and determining key prefecture-level city water catchment unit data from the prefecture-level city water catchment unit data based on the constructed water ecological environment problem index system; A water ecological environment problem data set is generated based on the determined key prefecture-level city water catchment units and the water ecological environment problem indicators corresponding to the key prefecture-level city water catchment units.

2. According to claim 1, the water ecological environment problem diagnosis method based on watershed spatial tracking and city spatial refinement, It is characterized in that The acquisition of watershed unit data of the target area based on the resistance factor includes: Identify and generalize water systems; Determine the control section, and based on the water system generalization results, calculate the watershed catchment range corresponding to the section through the minimum path resistance value; Based on the geographic space boundary fitting technology, the administrative responsibility boundary and the watershed catchment range are coupled to obtain the watershed catchment unit of the target area.

3. According to claim 2, the water ecological environment problem diagnosis method based on watershed spatial tracking and city spatial refinement, It is characterized in that The identification and generalization of water systems include: Collection of vector and raster data of target area; DEM data preprocessing; DEM extraction of river network; River network and water system verification.

4. According to claim 2, the water ecological environment problem diagnosis method based on watershed spatial tracking and city spatial refinement, It is characterized in that The control section is determined based on the water system generalization result, and the watershed catchment range corresponding to the section is calculated by the minimum path resistance value, including: Divide the target area into grids, perform weight analysis on the resistance factors using the analytic hierarchy process according to different terrains including plains, hills and mountains, obtain the weight value of each resistance factor of the corresponding terrain, and obtain the resistance coefficient for each spatial grid through weighted calculation; Establish a minimum resistance cumulative consumption distance model and calculate the plastic flow direction and path of the fluid particles in the space based on the resistance coefficient of each spatial grid, so as to obtain the minimum cost path from the source to the end; Based on the minimum cost path, the watershed catchment area corresponding to the section is obtained.

5. According to claim 4, the water ecological environment problem diagnosis method based on watershed spatial tracking and city spatial refinement, It is characterized in that The minimum resistance cumulative consumption distance model is: Where D ij is the spatial distance from source unit i to sink unit j; R i is the resistance coefficient in the transition process from source unit i to sink unit j; R i Depending on the value of i, the path from unit i to unit j produces different resistance values. When i is determined, calculating MCR requires selecting the path with the smallest resistance value in the spatial distance. This path conforms to the law of liquid flow and is the easiest path for runoff diffusion.

6. According to claim 1, the water ecological environment problem diagnosis method based on watershed spatial tracking and city spatial refinement, It is characterized in that A spatial autocorrelation statistical analysis is conducted on the concentrations of characteristic pollutants in the watershed units of the target area to identify and obtain watersheds with prominent water environment problems, including a spatial correlation analysis of characteristic pollutants in the watershed units of the target area based on the local Moran's index, where the characteristic pollutants include chemical oxygen demand, ammonia nitrogen and total phosphorus.

7. The water ecological environment problem diagnosis method based on watershed spatial tracking and city spatial refinement according to claim 6, It is characterized in that The formula for the local Moran's index is: In the formula, is the local Moran index, and Represent the attribute values ​​of units i and j respectively, is the mean of all unit attribute values, is the variance, Represents the spatial weight matrix, which is used to quantify the strength of the spatial relationship between i and j.

8. A device, It is characterized in that It includes a watershed catchment unit data acquisition module, a watershed identification module with prominent water environment problems, a prefecture-level city catchment unit data acquisition module, a key prefecture-level city catchment unit data determination module, and a water ecological environment problem data set generation module; Among them, the watershed catchment unit data acquisition module is used to obtain the watershed catchment unit data of the target area based on the resistance factor; The module for identifying watersheds with prominent water environment problems conducts spatial autocorrelation statistical analysis on the concentration of characteristic pollutants in the catchment units of the target area to identify and obtain watersheds with prominent water environment problems; A prefecture-level city water catchment unit data acquisition module is used to refine the water catchment unit of the watershed based on the prominent watershed of the water environment problem obtained, taking the prefecture-level city as the basic unit, and obtain the prefecture-level city water catchment unit data; A key prefecture-level city water catchment unit data determination module is used to construct a water ecological environment problem evaluation index system, and determine the key prefecture-level city water catchment unit data from the prefecture-level city water catchment unit data based on the constructed water ecological environment problem index system; The water ecological environment problem data set generation module is used to generate a water ecological environment problem data set based on the determined water catchment unit data of the key cities and the water ecological environment problem indicators corresponding to the water catchment units of the key cities.

9. A device comprising a memory, a processor and a computer program stored in the memory, It is characterized in that The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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