Method for assessing impact of river pollution in flood season by combining spatial analysis of river basin and water ecological response

Abstract

The present application relates to the technical field of river basin water environment management and water ecological evaluation, and particularly relates to a river flood season pollution impact evaluation method and system combining river basin spatial analysis and water ecological response. The method first collects water ecological data, pre-processes the water ecological data, calculates the water ecological metabolism background value before the non-flood season or the flood season pollution event based on the diurnal variation model of river dissolved oxygen concentration based on mass balance, calculates the theoretical lag time from rainfall to pollution peak value based on the correlation between the catchment area and the response time, and delimits the flood season pollution event window period. Based on the high-frequency monitoring data of the water ecology in the flood season pollution event window period, the water ecological metabolism response index is calculated, the disturbance intensity of the pollution event on the water ecological system metabolism function is evaluated, the non-point source pollution intensity index and the point source risk evaluation value are calculated, and the pollution source investigation suggestion is comprehensively generated. The present application effectively solves the problem of difficult definition of non-point source pollution responsibility in the flood season, and realizes the accurate identification of pollution sources.

Description

Technical Field

[0001] This invention relates to the field of watershed water environment management and water ecology assessment technology, and in particular to a method and system for assessing the pollution impact of rivers during the flood season that integrates watershed spatial analysis and water ecology response. Background Technology

[0002] In recent years, with the deepening of point source pollution control, non-point source pollution during the flood season has become a key issue restricting the continuous improvement of water quality in many river basins in my country. According to the data of the top 50 monitoring sections nationwide released by the Ministry of Ecology and Environment in 2022, the pollution intensity during the flood season reached a maximum of 17.69, which is equivalent to the peak concentration of the primary pollutant being 17.69 times the assessment target limit, highlighting the severity and prevalence of pollution during the flood season.

[0003] Currently, the management of river pollution during the flood season mainly faces the following three technical bottlenecks:

[0004] 1. Difficulty in Defining Administrative Liability for Non-point Source Pollution During the Flood Season: Non-point source pollution is characterized by randomness, dispersion, and lag. Existing technologies and methods are still insufficient in integrating multi-source spatial data such as natural conditions and human activities, and in conducting watershed-scale source-sink correlation analysis, making it difficult to accurately identify and define specific pollution liability entities. Local governments are often forced to adopt a "safety net" approach to remediation, such as unnecessary upgrades to sewage treatment facilities, which not only has low remediation efficiency but also increases administrative and social costs.

[0005] 2. A systematic approach to water ecological protection and management for integrated water management has not yet been established: the water ecological baseline is unclear, the data foundation is weak, prominent water ecological problems are difficult to identify accurately, and the existing management system aimed at pollution control and water quality improvement is no longer adequate to meet the needs of water ecological protection. For example, new indicators such as "flood season pollution intensity" proposed based on the health of the water ecosystem lack clear control requirements and work directions in actual management, which restricts the coordinated management of both water quality and water ecology objectives.

[0006] 3. Insufficient methods for identifying the water ecological impacts of flood season pollution: Existing assessment methods for potential changes in downstream water ecological functions caused by flood season pollution largely rely on structural indicators such as species composition. These methods are not only costly to analyze, but also have relatively limited application scope and representativeness, making it difficult to comprehensively and dynamically reflect the actual impact of short-term pollution shocks on the aquatic ecosystem. This hinders timely and accurate diagnosis of water ecological risks and the development of targeted remediation measures. Summary of the Invention

[0007] The present invention aims to at least partially solve one of the technical problems in the related art.

[0008] Therefore, the first objective of this invention is to propose a method for assessing the pollution impact of rivers during the flood season that integrates watershed spatial analysis and water ecological response, the steps of which include: S1. Collect water ecological data, preprocess the water ecological data, and use the processed data to calculate the water ecological metabolic background value before the non-flood season or flood season pollution event based on the mass balance river dissolved oxygen concentration diurnal variation model. The water ecological metabolic background value includes the water ecological metabolic response index. S2, based on the correlation between catchment area and response time, calculates the theoretical lag time from rainfall to pollution peak, and integrates the actual water quality peak occurrence time to delineate the flood season pollution event window period; S3. Based on the high-frequency monitoring data of water ecology during the flood season pollution event window, calculate the water ecology metabolic response index based on the diurnal variation model of river dissolved oxygen concentration in mass balance, and assess the intensity of the disturbance of the pollution event on the metabolic function of the water ecosystem based on the degree of deviation between the water ecology metabolic response index and the pre-obtained water ecology metabolic response index. S4. Based on the pollution event window period during the flood season and the spatial data of the catchment area, calculate the non-point source pollution intensity index and the point source risk assessment value, and comprehensively generate pollution source investigation suggestions.

[0009] In one embodiment of the present invention, S2 further includes: S21. Identify the catchment area of ​​the target section based on digital elevation model data, and calculate the theoretical lag time from rainfall to pollution peak based on the correlation between catchment area and response time. S22 integrates the actual peak water quality occurrence time to identify the effective rainfall impact period and delineate the flood season pollution event window period.

[0010] In one embodiment of the present invention, S3 further includes: S31. During the flood season pollution event window, identify the peak concentration of each pollutant, calculate its pollution index relative to the water quality assessment target limit, and define the maximum pollution index as the flood season pollution intensity of the event. S32, calculate the water ecological metabolic balance index during the flood season pollution event window period, and compare the water ecological metabolic response index during the flood season pollution event window period with the water ecological metabolic response index in the background value; S33. Assess the intensity of disturbance to the metabolic balance of the aquatic ecosystem caused by pollution events based on the degree of deviation between the water ecological metabolic response index during the flood season pollution event window period and the water ecological metabolic response index in the background value.

[0011] In one embodiment of the present invention, the core equation of the diurnal variation model of river dissolved oxygen concentration based on mass balance is: ; Among them, O i,d Dissolved oxygen concentration, For its rate of change, GPP d and ER d These are the total primary productivity and ecosystem respiration rate on day d, respectively, K600. d The gas exchange coefficient, i,d For the average water depth, PPFD i,d Photosynthetic photon flux density For PPFD i,d The daily average, Osat i,d This represents the dissolved oxygen saturation concentration.

[0012] In one embodiment of the present invention, S4 further includes: S41. Based on the spatial distribution of land use types in the catchment area and combined with the human activity intensity assignment method, calculate the non-point source pollution intensity index of each spatial unit. S42. For stationary pollution sources, the peak pollution index relative to the corresponding limit in the existing emission standards is calculated based on the peak concentration of pollutants during the pollution event window period in the flood season, and is used as the point source risk assessment value. S43 generates pollution source investigation suggestions based on area source and point source risks.

[0013] In one embodiment of the present invention, the method for calculating the non-point source pollution intensity index in step S41 is as follows: For different land use types, corresponding basic pollution load weights are set, and a human activity intensity correction coefficient based on regional statistical data is introduced. The area proportion of each land use type is multiplied by its corresponding basic pollution load weight and human activity intensity correction coefficient, and the results are added together to obtain the non-point source pollution intensity index.

[0014] In one embodiment of the present invention, the method for obtaining the point source risk assessment value in step S42 is as follows: Calculate the ratio of the peak concentration of various pollutants emitted by stationary pollution sources during the flood season pollution event window to the maximum allowable emission concentration limit in the corresponding limits of the existing emission standards. The maximum value of the ratio is used as the point source risk assessment value.

[0015] In one embodiment of the present invention, the method for preprocessing aquatic ecological data in step S1 includes: S11: Data cleaning is performed based on turbidity threshold and conductivity threshold. When the turbidity value of the data is greater than the turbidity threshold or the conductivity value is greater than the conductivity threshold, the data is judged to be high interference data and is removed. S12: When the observed data is lower than the annual minimum observed data threshold, the location is judged as a seriously missing location and is removed.

[0016] To achieve the above objectives, a second aspect of the present invention proposes a river flood season pollution impact assessment system that integrates watershed spatial analysis and water ecological response, comprising: The data acquisition module is used to collect aquatic ecological data, preprocess the aquatic ecological data, and use the processed data to calculate the aquatic ecological metabolic background value before pollution events during non-flood seasons or flood seasons based on the diurnal variation model of river dissolved oxygen concentration in mass balance. The aquatic ecological metabolic background value includes the aquatic ecological metabolic response index. The flood season pollution event window period segmentation module is used to calculate the theoretical lag time from rainfall to pollution peak based on the correlation between catchment area and response time, and to delineate the flood season pollution event window period by integrating the actual water quality peak occurrence time; The water ecological function disturbance intensification quantitative assessment module is used to calculate the water ecological metabolic response index based on the high-frequency monitoring data of water ecology during the flood season pollution event window, based on the diurnal variation model of river dissolved oxygen concentration in mass balance, and to assess the intensity of disturbance of the water ecological metabolic response index to the metabolic function of the water ecosystem based on the degree of deviation between the water ecological metabolic response index and the pre-obtained water ecological metabolic response index. The pollution source investigation suggestion generation module is used to calculate the non-point source pollution intensity index and point source risk assessment value based on the pollution event window period of the flood season and the spatial data of the catchment area, and to generate pollution source investigation suggestions in a comprehensive manner.

[0017] To achieve the above objectives, a third aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in the first aspect.

[0018] The methods, systems, and storage media of this invention provide a method that quantitatively assesses the disturbance of flood season pollution to aquatic ecological functions by calculating the background of aquatic ecological metabolism and the response during the event period. By establishing a spatiotemporal correlation framework of rainfall-runoff-pollution, it provides spatial analysis basis for identifying non-point source pollution sources and defining responsibility. Furthermore, by integrating spatial analysis of non-point source intensity with benchmarking against point source emission standards, it forms clearly identifiable clues for pollution source investigation. This invention integrates aquatic ecological function assessment and watershed spatial analysis technologies, providing a systematic analytical framework and quantitative basis for identifying the main source areas of flood season pollution and assessing its ecological impact, thus helping to improve the targeting and scientific nature of flood season pollution control.

[0019] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0020] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a method for assessing the pollution impact of rivers during the flood season that integrates watershed spatial analysis and water ecological response, according to an embodiment of this application. Figure 2 This application provides a spatial distribution map of river pollution intensity during the flood season in a certain area. Figure 3 Total productivity and respiration rate during the flood season and rainy / dry season, as provided in the embodiments of this application; Figure 4 A scatter plot showing the relationship between the non-point source pollution intensity index of the catchment area and the pollution intensity during the flood season, provided in an embodiment of this application; Figure 5 This is a structural diagram of a river flood season pollution impact assessment system that integrates watershed spatial analysis and water ecological response, provided as an embodiment of this application. Detailed Implementation

[0021] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0022] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0023] The following describes, with reference to the accompanying drawings, a method for assessing the pollution impact of rivers during the flood season that integrates watershed spatial analysis and water ecological response, according to an embodiment of the present invention.

[0024] Example 1 Figure 1 This is a flowchart of a method for assessing the pollution impact of rivers during the flood season that integrates watershed spatial analysis and water ecological response, according to an embodiment of the present invention.

[0025] like Figure 1 As shown, the method for assessing the pollution impact of this river during the flood season includes the following steps: S1. Collect water ecological data, preprocess the water ecological data, and use the processed data to calculate the water ecological metabolic background value before pollution events during non-flood seasons or flood seasons based on the diurnal variation model of river dissolved oxygen concentration in mass balance. The water ecological metabolic background value includes the water ecological metabolic response index.

[0026] Specifically, the water ecological data includes hydrological, water quality, and meteorological monitoring data of the target section. After the data collection is completed, the hydrological, water quality, and meteorological monitoring data of the target section are cleaned to remove missing data and abnormal interference.

[0027] In this invention, data cleaning is performed based on turbidity and conductivity thresholds. When the turbidity value or conductivity value exceeds the turbidity threshold or conductivity threshold, the data is identified as high-interference data and discarded. As one implementation, this invention sets the turbidity threshold to 500 NTU and the conductivity threshold to 3000 μS / cm.

[0028] Simultaneously, when the observed data falls below the annual minimum observation data threshold, the location is identified as a severely under-observed location and removed from the list. As one implementation method, this invention sets the minimum observation data threshold to 100 data points.

[0029] Based on historical high-frequency dissolved oxygen, water temperature, water depth, and photosynthetically active radiation data from the cleaned data, a diurnal variation model of river dissolved oxygen concentration based on mass balance was adopted. The prior distribution of key parameters was determined in conjunction with literature. The Metropolis-Hastings algorithm was used for sampling. Bayesian inference and Markov Chain Monte Carlo (MCMC) methods were used to calculate the water ecological metabolic background values ​​for typical periods before pollution events during non-flood seasons or flood seasons.

[0030] The core equation of the diurnal variation model of dissolved oxygen concentration in rivers based on mass balance is: ; Where Oi,d is the dissolved oxygen concentration at time i on day d. Let GPPd and ERd be the total primary productivity and ecosystem respiration rate on day d, respectively, and K600d be the gas exchange coefficient. i,d represents the average water depth, and PPFDi,d represents the photosynthetic photon flux density. It is its daily average value, and Osati,d is the dissolved oxygen saturation concentration.

[0031] Each Bayesian metabolic model was run on four MCMC chains, including 1000 warm-up iterations and 3000 sampling iterations. Convergence was verified using the Gelman-Rubin standard. Statistical measures are used for judgment. Based on this model, the GPP / ER index, which characterizes the metabolic balance of aquatic ecosystems, can be calculated as a baseline for subsequent assessments of aquatic ecological functions.

[0032] S2, based on the correlation between catchment area and response time, calculates the theoretical lag time from rainfall to pollution peak, and integrates the actual water quality peak occurrence time to delineate the flood season pollution event window period.

[0033] Based on digital elevation model data, the spatial extent of the catchment area where the target monitoring section is located is identified. The empirical relationship between catchment area and pollution response time is then utilized. T=k×A b ; Where k is the runoff time coefficient, T is the lag time (in hours) from rainfall to the occurrence of pollution peak at the cross section, A is the catchment area (km²) identified in step S2, and b is the size index.

[0034] Specifically, the confluence time coefficient k describes the intensity of the influence of the physical and geographical characteristics of a specific watershed on the response time. Its value ranges from 0.3 to 1.5, depending on multiple factors such as watershed slope, soil permeability, vegetation cover, and rainfall intensity. For small mountain watersheds with steep slopes and rapid flows, the coefficient may be relatively small (e.g., 0.3–0.6); for large watersheds with gentle terrain and significant water retention, the coefficient may be relatively large (e.g., 1.0–1.5). The case study uses an empirical value of 0.8, reflecting that the study area is a typical watershed with a moderate slope, common surface cover types (e.g., mixed forest, agricultural land, or medium-density urban areas), and a slightly meandering river channel.

[0035] The scale exponent b describes the nonlinear rate at which the response time (T) changes with the scale of the catchment area (A), ranging from 0.4 to 0.6, depending on factors such as watershed topography, river slope, and land cover. For watersheds with steep terrain and straight channels, the exponent may be lower (close to 0.4); for watersheds with flat terrain and meandering channels, the exponent may be higher (close to 0.6). The case study uses an empirical value of 0.5, based on the assumption of a standardized scaling relationship.

[0036] In one implementation method, k is set to 0.8 and b is set to 0.5. The formula used in this invention is as follows: T = 0.8 × A 0.5 .

[0037] By combining the measured peak water quality time, the effective rainfall impact period is determined in reverse, and then the window period for pollution events during the flood season is delineated.

[0038] S3. Based on the high-frequency monitoring data of water ecology during the flood season pollution event window, calculate the water ecology metabolic response index based on the diurnal variation model of river dissolved oxygen concentration in mass balance, and assess the intensity of the disturbance of the pollution event on the metabolic function of the water ecosystem based on the degree of deviation between the water ecology metabolic response index and the pre-obtained water ecology metabolic response index.

[0039] Based on the flood season pollution event window period defined in step S2, the peak concentration of each pollutant is identified, and its single-factor pollution index relative to the water quality assessment target limit is calculated. This index is defined as the ratio of the pollutant peak concentration to the standard limit. If a clear assessment target is lacking, it is recommended to use the "Surface Water Environmental Quality Standard" (GB 3838). The corresponding category limit in 2002 is the benchmark.

[0040] PI j = ; Among them, C peak,j C represents the peak concentration of pollutant j. standard,j Set its corresponding assessment target limit. The largest PI among each pollutant... j Defined as the flood season pollution intensity index for this event, it reflects the overall severity of the pollution event.

[0041] For the same flood season pollution event window period defined in step S2, the water ecological metabolic balance index (GPP / ER) for that period is calculated using the model in step S101. event And compare it with the background period index (GPP / ER). background By comparing these values, the extent to which a pollution event disrupts metabolic balance can be quantitatively assessed. An index value of 1 indicates that the system is in metabolic equilibrium; the greater the deviation from 1, the more the system deviates from equilibrium.

[0042] S4. Based on the pollution event window period during the flood season and the spatial data of the catchment area, calculate the non-point source pollution intensity index and the point source risk assessment value, and comprehensively generate pollution source investigation suggestions.

[0043] Based on the spatial distribution of land use types within the catchment area and combined with the human activity intensity assignment method, the non-point source pollution intensity index of each spatial unit is calculated: NSI = Σ ( A k × W k × α k ); Among them, A k W represents the area percentage of the k-th land use type. k For its basic pollution load weight, α kThe human activity intensity is adjusted using the following formula: The human activity intensity of land use type and its corresponding weight are set as follows: 0 for unused land and other naturally unused land; 0.25 for naturally regenerated land such as forest land, grassland, and water area; 0.5 for human regenerated land such as paddy field and dry land; and 1 for human non-regenerated land such as urban, rural, industrial, mining, and transportation land.

[0044] For stationary point sources (such as wastewater treatment plants and industrial discharge outlets), calculate their peak pollution index during the flood season pollution event window: ; Among them, C peak,m C represents the peak concentration of pollutant m. standard,m The corresponding limits are specified in the "Discharge Standard of Pollutants for Municipal Wastewater Treatment Plants" (GB 18918-2002) and its amendments.

[0045] By combining the area source intensity index and the point source peak pollution index, a list of pollution source investigation recommendations is generated, providing spatial guidance and priority basis for pollution prevention and control during the flood season.

[0046] As one implementation method, the method for generating the recommendation list in this invention is as follows: based on data such as land use, activity intensity, and key pollution source emission data of the catchment area where the target section is located, calculate the non-point source intensity index and the point source peak pollution index and sort them to generate recommendations for investigating pollution sources such as non-point sources and point sources.

[0047] To facilitate understanding of the evaluation method in this application that integrates watershed spatial analysis and water ecological response, the following is combined with... Figures 2 to 4 This study, focusing on a city in my country, collected data from over 100 monitoring sections, retaining 125 valid monitoring stations after data cleaning. Analysis revealed that the average pollution intensity during the flood season at all stations was 7.86, with a peak value of 28.25. The spatial distribution of these values ​​is shown in the figure. Figure 2 A comprehensive analysis of the water ecology during typical flood season pollution event windows was conducted. Figure 3The study found that during this period, gross primary productivity (GPP) was significantly lower than the average levels during the flood season and non-flood season by 90% and 91%, respectively; while ecosystem respiration rate (ER) was higher by 5% and 39%, respectively, resulting in a significant 94% decrease in the water ecological metabolic balance index GPP / ER compared to the non-flood season level. This indicates that the flow shock caused by flood season pollution events inhibited autotrophic production processes represented by GPP, while simultaneously stimulating heterotrophic respiration processes represented by ER through excessive nutrient input, leading to a severe imbalance in water ecological metabolism and an exacerbation of the aquatic ecosystem's shift towards a heterotrophic state. Furthermore, based on 10-meter resolution land use data, the intensity of human activities was interpreted, and the non-point source pollution intensity was calculated in conjunction with the pollution source inventory. Spatial overlay analysis of this intensity with the flood season pollution intensity revealed a significant positive correlation between the two. Figure 4 This finding confirms that human activities exacerbate watershed pollution loads, while flood season pollution further intensifies the imbalance of aquatic ecosystems. This method ultimately outputs detailed recommendations for investigation areas down to the discharge outlet scale, supporting management departments in identifying and prioritizing high-risk areas for flood season pollution and determining the order of priority for investigation.

[0048] In summary, this application's embodiments, by integrating high-frequency monitoring data, aquatic ecological metabolism models, catchment area spatial analysis, and human activity intensity assessment, construct a comprehensive flood season pollution impact assessment method covering the entire chain from "pollution process identification to aquatic ecological function assessment to pollution source investigation." This method not only achieves quantitative assessment of flood season pollution intensity but also identifies the actual impact of pollution on the metabolic functions of aquatic ecosystems, providing spatial and quantitative technical support for the determination and investigation of responsibility for non-point source and point source pollution. Case studies demonstrate that this method has high practicality and reliability in identifying high-incidence pollution areas, analyzing the impact of human activities, and assessing aquatic ecological effects, providing a scientific basis for river flood season pollution prevention and control and aquatic ecological protection.

[0049] Example 2 Figure 5 This is a structural diagram of a river flood season pollution impact assessment system that integrates watershed spatial analysis and water ecological response, according to an embodiment of the present invention.

[0050] The data acquisition module is used to collect aquatic ecological data, preprocess the aquatic ecological data, and use the processed data to calculate the aquatic ecological metabolic background value before pollution events during non-flood seasons or flood seasons based on the diurnal variation model of river dissolved oxygen concentration in mass balance. The aquatic ecological metabolic background value includes the aquatic ecological metabolic response index.

[0051] The data acquisition module includes a preprocessing unit that cleans the data based on turbidity and conductivity thresholds. When the turbidity value or conductivity value is greater than the turbidity threshold or conductivity threshold, the data is identified as high-interference data and is removed.

[0052] The data acquisition module also includes a water ecological metabolism background value calculation unit, which calculates the water ecological metabolism background value based on the diurnal variation model of river dissolved oxygen concentration in mass balance.

[0053] The module for defining pollution event windows during the flood season is used to calculate the theoretical lag time from rainfall to pollution peak based on the correlation between catchment area and response time, and to define pollution event windows by integrating the actual water quality peak occurrence time.

[0054] Specifically, the flood season pollution event window period delineation module includes a theoretical lag time calculation unit and a flood season pollution event window period calculation unit. The theoretical lag time calculation unit is used to identify the catchment area of ​​the target section based on digital elevation model data, and calculate the theoretical lag time from rainfall to the pollution peak based on the correlation between the catchment area and the response time. The flood season pollution event window period calculation unit is used to integrate the actual water quality peak occurrence time, identify the effective rainfall impact period, and delineate the flood season pollution event window period.

[0055] The water ecological function disturbance intensity quantification module calculates the water ecological metabolic response index based on the high-frequency monitoring data of water ecology during the flood season pollution event window, and calculates the water ecological metabolic response index based on the diurnal variation model of river dissolved oxygen concentration in mass balance. Based on the deviation of the water ecological metabolic response index from the pre-obtained water ecological metabolic response index, the module assesses the disturbance intensity of the pollution event on the metabolic function of the water ecosystem.

[0056] The water ecological function disturbance intensity quantification module includes a flood season pollution intensity calculation unit, a water ecological metabolic balance index calculation unit, and a disturbance intensity determination unit.

[0057] The flood season pollution intensity calculation unit is used to identify the peak concentration of each pollutant during the flood season pollution event window, calculate its pollution index relative to the water quality assessment target limit, and define the maximum pollution index as the flood season pollution intensity of the event.

[0058] The water ecological metabolic balance index calculation unit is used to calculate the water ecological metabolic balance index during the flood season pollution event window period and compare the water ecological metabolic response index during the flood season pollution event window period with the water ecological metabolic response index in the background value. The disturbance intensity determination unit is used to assess the disturbance intensity of a pollution event on the metabolic balance of the aquatic ecosystem based on the degree of deviation between the water ecological metabolic response index during the flood season pollution event window and the water ecological metabolic response index in the background value.

[0059] The pollution source investigation suggestion generation module calculates the non-point source pollution intensity index and point source risk assessment value based on the pollution event window period of the flood season and the spatial data of the catchment area, and generates pollution source investigation suggestions in a comprehensive manner.

[0060] Specifically, the pollution source investigation suggestion generation module includes a point source risk assessment unit and a non-point source pollution index calculation unit. The non-point source pollution index calculation unit is used to calculate the non-point source pollution intensity index for each spatial unit. The calculation formula is as follows: NSI = Σ ( A k × W k × α k ); Among them, A k W represents the area percentage of the k-th land use type. k For its basic pollution load weight, α k It is a correction factor for the intensity of human activities.

[0061] The point source risk assessment unit is used to calculate the ratio of the peak concentration of various pollutants emitted by stationary pollution sources during the flood season pollution event window to the maximum allowable emission concentration limit in the corresponding limits of the existing emission standards. The maximum value of the ratio is used as the point source risk assessment value.

[0062] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned method for assessing the pollution impact of rivers during the flood season by integrating watershed spatial analysis and water ecological response.

[0063] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0064] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. A method for assessing the pollution impact of rivers during the flood season that integrates watershed spatial analysis and water ecological response, characterized by the following steps: include: S1. Collect water ecological data, preprocess the water ecological data, and use the processed data to calculate the water ecological metabolic background value before the non-flood season or flood season pollution event based on the mass balance river dissolved oxygen concentration diurnal variation model. The water ecological metabolic background value includes the water ecological metabolic response index. S2, based on the correlation between catchment area and response time, calculates the theoretical lag time from rainfall to pollution peak, and integrates the actual water quality peak occurrence time to delineate the flood season pollution event window period; S3. Based on the high-frequency monitoring data of water ecology during the flood season pollution event window, calculate the water ecology metabolic response index based on the diurnal variation model of river dissolved oxygen concentration in mass balance, and assess the intensity of the disturbance of the pollution event on the metabolic function of the water ecosystem based on the degree of deviation between the water ecology metabolic response index and the pre-obtained water ecology metabolic response index. S4. Based on the monitoring data of the pollution event window period during the flood season and the spatial data of the catchment area, calculate the non-point source pollution intensity index and the point source risk assessment value, and generate pollution source investigation suggestions in a comprehensive manner.

2. The method according to claim 1, characterized in that, S2 further includes: S21. Identify the catchment area of ​​the target section based on digital elevation model data, and calculate the theoretical lag time from rainfall to pollution peak based on the correlation between the catchment area and response time. S22 integrates the actual peak water quality occurrence time to identify the effective rainfall impact period and delineate the flood season pollution event window period.

3. The method according to claim 1, characterized in that, S3 further includes: S31. During the flood season pollution event window, identify the peak concentration of each pollutant, calculate its pollution index relative to the water quality assessment target limit, and define the maximum pollution index as the flood season pollution intensity of the event. S32, calculate the water ecological metabolic balance index during the flood season pollution event window period, and compare the water ecological metabolic response index during the flood season pollution event window period with the water ecological metabolic response index in the background value; S33. Assess the intensity of disturbance to the metabolic balance of the aquatic ecosystem caused by pollution events based on the degree of deviation between the water ecological metabolic response index during the flood season pollution event window period and the water ecological metabolic response index in the background value.

4. The method according to claim 1, characterized in that, The core equation of the diurnal variation model of river dissolved oxygen concentration based on mass balance is: ； Among them, O i,d Dissolved oxygen concentration, For its rate of change, GPP d and ER d These are the total primary productivity and ecosystem respiration rate on day d, respectively, K600. d The gas exchange coefficient, i,d For the average water depth, PPFD i,d Photosynthetic photon flux density For PPFD i,d The daily average, Osat i,d This represents the dissolved oxygen saturation concentration.

5. The method according to claim 1, characterized in that, S4 further includes: S41. Based on the spatial distribution of land use types in the catchment area and combined with the human activity intensity assignment method, calculate the non-point source pollution intensity index of each spatial unit. S42. For stationary pollution sources, the peak pollution index relative to the corresponding limit in the existing emission standards is calculated based on the peak concentration of pollutants during the pollution event window period in the flood season, and is used as the point source risk assessment value. S43 generates pollution source investigation suggestions based on area source and point source risks.

6. The method according to claim 5, characterized in that, The method for calculating the area source pollution intensity index in step S41 is as follows: For different land use types, corresponding basic pollution load weights are set, and a human activity intensity correction coefficient based on regional statistical data is introduced. The area proportion of each land use type is multiplied by its corresponding basic pollution load weight and human activity intensity correction coefficient, and the results are added together to obtain the non-point source pollution intensity index.

7. The method according to claim 5, characterized in that, The method for obtaining the point source risk assessment value in step S42 is as follows: Calculate the ratio of the peak concentration of various pollutants emitted by stationary pollution sources during the flood season pollution event window to the maximum allowable emission concentration limit in the corresponding limits of the existing emission standards. The maximum value of the ratio is used as the point source risk assessment value.

8. The method according to claim 1, characterized in that, The method for preprocessing aquatic ecological data described in step S1 includes: S11: Data cleaning is performed based on turbidity threshold and conductivity threshold. When the turbidity value of the data is greater than the turbidity threshold or the conductivity value is greater than the conductivity threshold, the data is judged to be high interference data and is removed. S12: When the observed data is lower than the annual minimum observed data threshold, the location is judged as a seriously missing location and is removed.

9. A river flood season pollution impact assessment system integrating watershed spatial analysis and water ecological response, characterized in that, include: The data acquisition module is used to collect aquatic ecological data, preprocess the aquatic ecological data, and use the processed data to calculate the aquatic ecological metabolic background value before pollution events during non-flood seasons or flood seasons based on the diurnal variation model of river dissolved oxygen concentration in mass balance. The aquatic ecological metabolic background value includes the aquatic ecological metabolic response index. The flood season pollution event window period segmentation module is used to calculate the theoretical lag time from rainfall to pollution peak based on the correlation between catchment area and response time, and to delineate the flood season pollution event window period by integrating the actual water quality peak occurrence time; The water ecological function disturbance intensity quantification module is used to calculate the water ecological metabolic response index based on the high-frequency monitoring data of water ecology during the flood season pollution event window, and based on the diurnal variation model of river dissolved oxygen concentration in mass balance, and to assess the disturbance intensity of the pollution event on the metabolic function of the water ecosystem based on the deviation of the water ecological metabolic response index from the pre-obtained water ecological metabolic response index. The pollution source investigation suggestion generation module is used to calculate the non-point source pollution intensity index and point source risk assessment value based on the pollution event window period of the flood season and the spatial data of the catchment area, and to generate pollution source investigation suggestions in a comprehensive manner.

10. A computer-readable storage medium storing a computer program that, when executed by a processor, implements the method as claimed in any one of claims 1-8.

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