A water environment bearing capacity evaluation and early warning analysis method

Abstract

The application discloses a water environment bearing capacity evaluation and early warning analysis method, relates to the technical field of water environment early warning, and generates a pollution load response data set Lrs, establishes a real corresponding relationship between pollution input and water quality change, avoids information distortion caused by bearing capacity judgment according to only a single point water quality index, continuously analyzes the pollution load response data set Lrs, forms a water quality response change data set Res, and makes the amplitude and change intensity of water quality response with pollution load change capable of being quantitatively identified, thereby providing reliable data support for subsequent trend judgment, calculates a pollution absorption saturation trend index Sat based on the water quality response change data set Res, reflects whether the change trend of pollution absorption capacity of the target water body appears amplification response in the process of gradually increasing pollution load, and thereby breaks through the problem that the linear hypothesis is generally used in the prior art and the pollution absorption capacity close to the saturation state is difficult to be identified in time.

Description

Technical Field

[0001] This invention relates to the field of water environment early warning technology, specifically a method for assessing and analyzing water environment carrying capacity. Background Technology

[0002] With the continuous increase in regional economic development and human activity intensity, the pollution load on water bodies is constantly changing. How to rationally assess the water environment's carrying capacity for pollution input under given water resource conditions has become a key issue in water environment management and ecological protection. Scientifically assessing the water environment's carrying capacity and achieving risk early warning based on the operational status of water bodies under different pollution pressures is one of the important research directions in the field of water environment management.

[0003] Current methods for assessing water environmental carrying capacity typically rely on a linear or near-linear relationship between pollution load and water quality indicators to calculate and determine the carrying capacity of water bodies. While these methods are applicable when pollution loads are low or fluctuate only slightly, in actual water environment operation, the absorption, transformation, and dilution capacity of water bodies for pollutants often exhibits significant nonlinear characteristics. Especially under conditions of long-term pollution input or high-intensity discharge, the physical, chemical, and biological processes within the water body gradually approach their limits, and the water quality response caused by unit changes in pollution load no longer maintains a linear relationship. Existing assessment methods fail to effectively characterize this transition from absorbability to near saturation, leading to significant biases in the assessment of the water environmental carrying capacity. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method for assessing and analyzing the carrying capacity of the water environment, thus solving the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for assessing and analyzing the carrying capacity of the water environment, comprising the following steps: S1. Collect pollution load data of the target water body during the historical operating cycle and water quality response data corresponding to the pollution load data, and integrate the pollution load data and the water quality response data based on the time correspondence to generate a pollution load response data set Lrs; S2. Analyze the pollution load response data set Lrs to obtain the characteristic information of water quality response changing with pollution load, and generate a water quality response change data set Res based on the characteristic information; S3. Based on the water quality response change data set Res, calculate the trend information of the target water body's pollution absorption capacity with the change of pollution load, and obtain the pollution absorption saturation trend index Sat. S4. Introduce the pollution absorption saturation trend index Sat into the water environment carrying capacity assessment process to correct the water environment carrying capacity assessment results, and generate a carrying capacity early warning result set War based on the corrected water environment carrying capacity status.

[0006] Preferably, S1 includes S11; S11. Taking the target water body as the object, the historical operating cycle is divided into multiple consecutive time periods according to the preset historical operating cycle; Within each time period, the corresponding pollution load data and the water quality response data that are time-matched with the pollution load data are acquired respectively; The pollution load data is used to reflect the input of pollutants into the target water body during the time period. The water quality response data is used to reflect the water quality changes of the target water body caused by the input of the pollutants during the time period. The data are then integrated to form a set of raw pollution load data arranged by time period and a set of raw water quality response data.

[0007] Preferably, S1 further includes S12; S12. Based on the original pollution load data set and the original water quality response data set, the pollution load data and water quality response data within the same time period are paired according to the time period correspondence. After pairing, the pollution load data and water quality response data corresponding to each time group are integrated to generate a data unit containing pollution load information and corresponding water quality response information. The multiple data units are aggregated in chronological order to form a pollution load response data set Lrs; The pollution load response data set Lrs is used to represent the correlation between different pollution load input conditions and corresponding water quality responses of the target water body during its historical operating cycle.

[0008] Preferably, S2 includes S21; S21. Using the pollution load response dataset Lrs as input data, process the data unit corresponding to each time period in sequence to construct the basic data of water quality response change for subsequent analysis. The process specifically includes steps S211, S212, and S213; S211. The pollution load data recorded in the data unit is summed up for all pollutant inputs within the time period to obtain pollution load level data representing the overall pollutant input intensity within the time period; the pollution load level data is used to represent the total amount of pollution input received by the target water body within the time period. S212. For the water quality response data recorded in the data unit, the average value of multiple water quality monitoring results obtained within the time period is calculated to obtain water quality response numerical data that represents the overall water quality status of the water body during the time period; the water quality response numerical data is used to reflect the comprehensive water quality response level of the target water body to the pollution load input during the time period. S213. Using the data units corresponding to two adjacent time periods as comparison objects, the water quality response numerical data in adjacent time periods are processed by difference to obtain the change results of water quality response between adjacent time periods, thereby forming water quality response change data. By repeating the above processing procedure on all adjacent data units in the pollution load response dataset Lrs, a dataset of water quality response change is formed.

[0009] Preferably, S2 further includes S22; S22. Based on the data set of water quality response changes, execute steps S221, S222 and S223 to extract the correlation features between water quality response changes and pollution load changes. S221. Based on all the obtained pollution load level data, first obtain the minimum and maximum values ​​in the pollution load level data to determine the overall numerical range of pollution load changes. Within the overall numerical range, the overall numerical range is divided into multiple consecutive pollution load intervals according to a preset interval number parameter; Each pollution load interval corresponds to a specific pollution load value range, which is used to collect water quality response change data where the pollution load level falls within that value range. S222. For each pollution load interval, extract all water quality response change data that fall within that pollution load interval. The average value of the water quality response change data is calculated to obtain the interval change intensity data representing the intensity of water quality response change within the pollution load interval; The interval variation intensity data is used to represent the overall level of water quality response variation under similar pollution load conditions; S223. Arrange and collect the interval change intensity data corresponding to different pollution load intervals in order of pollution load interval from low to high to form a water quality response change data set Res; The water quality response change data set Res is used to represent the correlation between the intensity of water quality response change and the level of pollution load.

[0010] Preferably, S3 includes S31; S31. Using the water quality response change data set Res as input data, extract the corresponding interval change intensity data in order of pollution load interval from low to high: take the interval change intensity data corresponding to two adjacent pollution load intervals as comparison objects, and obtain the increase data of water quality response change intensity between adjacent pollution load intervals by subtracting the interval change intensity data of the previous pollution load interval from the interval change intensity data of the latter pollution load interval. By repeating the above interval change intensity data for all adjacent pollution load intervals, a data set of water quality response change intensity growth is formed, which is used to represent the change in water quality response change intensity as the pollution load increases.

[0011] Preferably, S3 further includes S32; S32. Based on the data set of water quality response change intensity growth, perform a continuous analysis of the direction of change of the growth data according to the order of pollution load intervals; When the corresponding water quality response change intensity growth data are all greater than zero in multiple consecutive pollution load intervals, and the preset threshold for the number of growth intervals is met, the water quality response change intensity is marked as showing a continuous increasing trend, and it is determined that the pollution absorption capacity of the target water body continues to decrease with the increase of pollution load. When the corresponding water quality response change intensity growth data are all less than zero in multiple consecutive pollution load intervals, and the preset threshold for the number of decreasing intervals is met continuously, the water quality response change intensity is marked as showing a continuous decreasing trend, and it is determined that the target water body's pollution absorption capacity has not continuously decreased with the increase of pollution load. When the increase in water quality response intensity does not continuously meet the threshold for the number of increase intervals or the threshold for the number of decrease intervals, it is marked that the water quality response intensity does not show a unidirectional change trend.

[0012] Preferably, S3 further includes S33; S33. Based on the number of intervals that satisfy the continuous increasing trend and the continuous decreasing trend respectively in the data set of water quality response change intensity growth, and their distribution in the overall pollution load interval, perform trend summary processing to distinguish the direction of the interval growth data of continuous increasing trend and continuous decreasing trend, obtain trend result data, and form trend result data to represent the overall change direction and degree of water quality response change intensity. The trend results data are output as the pollution absorption saturation trend index, Sat. Among them, the pollution absorption saturation trend index Sat is a trend index that comprehensively reflects both the increasing and decreasing trend contributions of the water quality response intensity.

[0013] Preferably, S4 includes S41; S41. Based on the existing water environment assessment system, assess the current state of the target water body to obtain the benchmark bearing capacity state result used to represent the basic bearing condition of the target water body; The baseline bearing capacity state results are used as a reference basis for subsequent bearing capacity correction processing; The pollution absorption saturation trend index Sat is compared with the trend determination criteria used to determine the continuous increasing trend and the continuous decreasing trend. Based on the comparison results, the baseline carrying capacity state results are corrected to obtain the corrected water environment carrying capacity state. When the pollution absorption saturation trend index Sat meets the judgment condition corresponding to the continuous increase trend, it is determined that the pollution absorption capacity of the target water body is in a declining state, and the benchmark carrying capacity state result is linearly negatively corrected to reduce the carrying capacity judgment level of the target water body. When the pollution absorption saturation trend index Sat meets the judgment condition corresponding to the continuous decreasing trend, it is determined that the pollution absorption capacity of the target water body is in a relatively stable or improved state, and the benchmark carrying capacity state result is linearly positively corrected. When the pollution absorption saturation trend index Sat does not meet the judgment conditions of continuous increase or continuous decrease, the baseline carrying capacity state result remains unchanged and is used as the corresponding corrected water environment carrying capacity state.

[0014] Preferably, S4 further includes S42; S42. Based on the obtained corrected water environment carrying capacity status as the judgment basis, and the correspondence between it and the preset carrying risk judgment conditions, the target water body is divided into the corresponding carrying risk level. The risk levels are categorized into low-risk, medium-risk, and high-risk levels. When the modified water environment carrying capacity status falls within the judgment range corresponding to the low-risk carrying capacity level, the target water body is classified as a low-risk carrying capacity level. When the modified water environment carrying capacity status falls within the judgment range corresponding to the medium-risk carrying capacity level, the target water body will be classified as a medium-risk carrying capacity level. When the modified water environment carrying capacity status falls within the judgment range corresponding to the high-risk carrying capacity level, the target water body will be classified as a high-risk carrying capacity level. The identification information of the target water body, the corresponding corrected water environment carrying capacity status, and the determined carrying capacity risk level are collected as early warning output results to generate a carrying capacity early warning result set War.

[0015] This invention provides a method for assessing and providing early warning analysis of water environment carrying capacity, which has the following beneficial effects: (1) By generating a pollution load response data set Lrs, a true correspondence between pollution input and water quality changes is established, avoiding information distortion caused by relying solely on a single point-in-time water quality index for carrying capacity judgment. On this basis, through continuous analysis of the pollution load response data set Lrs, a water quality response change data set Res is formed, enabling quantitative identification of the magnitude and intensity of water quality response changes with pollution load, thus providing reliable data support for subsequent trend judgment. Furthermore, this method calculates the pollution absorption saturation trend index Sat based on the water quality response change data set Res, which can reflect whether the target water body's pollution absorption capacity shows an amplified response trend during the gradual increase of pollution load, thereby overcoming the problem of the common use of linear assumptions in existing technologies and the difficulty in timely identifying pollution absorption capacity approaching saturation. Finally, by introducing the pollution absorption saturation trend index Sat into the water environment carrying capacity assessment process, the traditional water environment carrying capacity assessment results are corrected, and a carrying capacity early warning result set War is generated, so that the identification of carrying capacity risk no longer depends on the result judgment after the water quality index has obviously deteriorated, but can issue early warnings when the water quality is still within the standard range but the pollution absorption capacity has obviously decreased.

[0016] (2) By constructing a data set of water quality response change intensity growth and conducting a continuous analysis of the growth direction within adjacent pollution load intervals, it is possible to effectively distinguish whether the water quality response change is caused by occasional fluctuations or is the result of continuous amplification during the increase of pollution load, thereby avoiding the risk of misjudgment of water body carrying capacity deterioration based solely on a single change or local anomaly in existing technologies. On this basis, by summarizing the trend of the number and distribution of intervals that meet the continuous increasing trend and continuous decreasing trend, a pollution absorption saturation trend index Sat is formed, transforming the process of pollution absorption capacity approaching saturation from "post-event observation of water quality deterioration" to "early identification of change trends".

[0017] (3) By comparing the pollution absorption saturation trend index Sat with the trend judgment conditions, linear negative or linear positive corrections are applied to the baseline carrying capacity status results. This allows for the early downgrading of the carrying capacity judgment level of the target water body when the water quality has not deteriorated significantly but the pollution absorption capacity has continued to decline. This addresses the problem of the carrying capacity assessment results lagging behind actual risk changes in existing technologies. Based on this, by combining the corrected water environment carrying capacity status with preset carrying capacity risk judgment conditions, the target water body is divided into low-risk, medium-risk, or high-risk carrying capacity levels, and a carrying capacity early warning result set War is generated. This allows the water environment carrying capacity risk to be output intuitively in the form of graded early warnings. Attached Figure Description

[0018] Figure 1This is a schematic diagram of a water environment carrying capacity assessment and early warning analysis method according to the present invention. Detailed Implementation

[0019] 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. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0020] Example 1: This invention provides a method for assessing and analyzing the carrying capacity of the water environment for early warning. Please refer to [link / reference]. Figure 1 This includes the following steps: S1. Collect pollution load data of the target water body during the historical operating cycle and water quality response data corresponding to the pollution load data, and integrate the pollution load data and the water quality response data based on the time correspondence to generate a pollution load response data set Lrs; S2. Analyze the pollution load response data set Lrs to obtain the characteristic information of water quality response changing with pollution load, and generate a water quality response change data set Res based on the characteristic information; S3. Based on the water quality response change data set Res, calculate the trend information of the target water body's pollution absorption capacity with the change of pollution load, and obtain the pollution absorption saturation trend index Sat. S4. Introduce the pollution absorption saturation trend index Sat into the water environment carrying capacity assessment process to correct the water environment carrying capacity assessment results, and generate a carrying capacity early warning result set War based on the corrected water environment carrying capacity status.

[0021] In this embodiment, a pollution load response data set Lrs is generated to establish a true correspondence between pollution input and water quality changes, avoiding information distortion caused by relying solely on a single point-in-time water quality index for carrying capacity assessment. Based on this, continuous analysis of the pollution load response data set Lrs generates a water quality response change data set Res, enabling quantitative identification of the magnitude and intensity of water quality response changes with pollution load, thus providing reliable data support for subsequent trend assessment. Furthermore, this method calculates a pollution absorption saturation trend index Sat based on the water quality response change data set Res, reflecting whether the target water body's pollution absorption capacity exhibits an amplified response trend as the pollution load gradually increases. This overcomes the problem of existing technologies that commonly employ linear assumptions and struggle to promptly identify pollution absorption capacity approaching saturation. Finally, by introducing the pollution absorption saturation trend index Sat into the water environment carrying capacity assessment process, the traditional water environment carrying capacity assessment results are corrected, and a carrying capacity early warning result set War is generated. This allows the identification of carrying capacity risk to no longer rely on results after water quality indicators have significantly deteriorated, but rather to issue early warnings when water quality remains within acceptable limits but pollution absorption capacity has significantly decreased. For example, in actual river and lake management, when the total amount of pollution discharge does not change much but the pollution absorption saturation trend index Sat continues to increase, this method can still indicate that the target water body has an increasing risk of carrying capacity through the carrying capacity early warning result set War. This provides management departments with a window of opportunity for early intervention and regulation, reduces the probability of sudden deterioration of the water environment, and improves the scientificity and practicality of water environment carrying capacity assessment and early warning.

[0022] Example 2: Specifically: S1 includes S11; S11. Taking the target water body as the object, the historical operating cycle is divided into multiple consecutive time periods according to the preset historical operating cycle; Within each time period, the corresponding pollution load data and the water quality response data that are time-matched with the pollution load data are acquired respectively; The pollution load data is used to reflect the input of pollutants into the target water body during the time period. The water quality response data is used to reflect the water quality changes of the target water body caused by the input of the pollutants during the time period. The data is then integrated and processed to form a set of original pollution load data arranged by time period and a set of original water quality response data, providing a unified data foundation for subsequent data correlation processing. It should be noted that: Explanation of historical operating cycle: The historical operating cycle refers to the time range within which the target water body has recorded complete pollution load data and water quality response data. This time range can be selected as a continuous natural time period according to actual management needs to ensure the continuity and comparability of the data. Explanation regarding time period division: The time period is the smallest analytical unit formed by dividing the historical operating cycle into equal or non-equal intervals. Each time period should ensure that it contains at least one valid pollution load data record and a corresponding water quality response data record to ensure the effectiveness of subsequent time correlations.

[0023] S1 further includes S12; S12. Based on the original pollution load data set and the original water quality response data set, the pollution load data and water quality response data within the same time period are paired according to the time period correspondence. After pairing, the pollution load data and water quality response data corresponding to each time group are integrated to generate a data unit containing pollution load information and corresponding water quality response information. The multiple data units are aggregated in chronological order to form a pollution load response data set Lrs; The pollution load response data set Lrs is used to represent the correlation between different pollution load input conditions and corresponding water quality responses of the target water body during the historical operating cycle. It should be noted that: Explanation of time correspondence: The time correspondence refers to the correspondence between pollution load data and water quality response data occurring within the same time period, or within the allowable response delay range. The response delay range can be preset according to the hydrodynamic conditions of the target water body to ensure the causal relationship between pollution input and water quality changes. Explanation of data integration method: The integration refers to storing pollution load data and water quality response data within the same time period in the same data unit, while maintaining the time sequence information, so that implementers can trace the pollution input and water quality changes corresponding to any data unit.

[0024] In this embodiment, the target water body's operation process is divided into multiple consecutive time periods according to a preset historical operating cycle. Pollution load data and water quality response data are acquired synchronously within each time period. This avoids the problem of misalignment between pollution input and water quality changes caused by inconsistent monitoring times or scattered data sources in existing technologies. Furthermore, by pairing and integrating pollution load data and water quality response data within the same time period, a pollution load response data set Lrs is formed, arranged in chronological order. This ensures that each set of pollution inputs has a clearly corresponding water quality response result, providing a reliable basis for analyzing the actual impact of pollution load changes on water quality. For example, in actual watershed management, when industrial discharge load fluctuates in the short term, traditional methods often struggle to determine whether this fluctuation truly causes water quality changes. However, the pollution load response data set Lrs allows direct tracing of the relationship between pollution load changes and corresponding water quality responses within that time period, reducing misjudgments caused by time mismatches or data mixing, and providing more realistic and traceable data support for subsequent water environment carrying capacity assessments.

[0025] Example 3: Specifically: S2 includes S21; S21. Using the pollution load response dataset Lrs as input data, process the data unit corresponding to each time period in sequence to construct the basic data of water quality response change for subsequent analysis. The process specifically includes steps S211, S212, and S213; S211. The pollution load data recorded in the data unit is summed up for all pollutant inputs within the time period to obtain pollution load level data representing the overall pollutant input intensity within the time period; the pollution load level data is used to represent the total amount of pollution input received by the target water body within the time period. S212. For the water quality response data recorded in the data unit, the average value of multiple water quality monitoring results obtained within the time period is calculated to obtain water quality response numerical data that represents the overall water quality status of the water body during the time period; the water quality response numerical data is used to reflect the comprehensive water quality response level of the target water body to the pollution load input during the time period. S213. Using the data units corresponding to two adjacent time periods as comparison objects, the water quality response numerical data in adjacent time periods are processed by difference to obtain the change results of water quality response between adjacent time periods, thereby forming water quality response change data. By repeating the above processing procedure on all adjacent data units in the pollution load response data set Lrs, a water quality response change data set is formed; the water quality response change data set is used to represent the actual change magnitude of the water quality response during the process of pollution load change.

[0026] S2 further includes S22; S22. Based on the data set of water quality response changes, execute steps S221, S222 and S223 to extract the correlation features between water quality response changes and pollution load changes. S221. Based on all the obtained pollution load level data, first obtain the minimum and maximum values ​​in the pollution load level data to determine the overall numerical range of pollution load changes. Within the overall numerical range, the overall numerical range is divided into multiple consecutive pollution load intervals according to a preset interval number parameter; Each pollution load interval corresponds to a specific pollution load value range, which is used to collect water quality response change data where the pollution load level falls within that value range. S222. For each pollution load interval, extract all water quality response change data that fall within that pollution load interval. The average value of the water quality response change data is calculated to obtain the interval change intensity data representing the intensity of water quality response change within the pollution load interval; The interval variation intensity data is used to represent the overall level of water quality response variation under similar pollution load conditions; S223. Arrange and collect the interval change intensity data corresponding to different pollution load intervals in order of pollution load interval from low to high to form a water quality response change data set Res; The water quality response change dataset Res is used to represent the correlation between the intensity of water quality response change and the pollution load level. It should be noted that: The interval quantity parameter is a preset parameter used to control the fineness of the pollution load interval division. Its value can be set according to the sample size or variation range of the pollution load level data to ensure that each pollution load interval contains at least effective water quality response change data. The so-called equal division refers to dividing the range of pollution load level data into multiple continuous intervals according to the interval quantity parameter, so as to avoid subjective bias caused by manually setting interval boundaries. The interval change intensity data is a numerical result obtained by averaging the water quality response change data within the same pollution load interval, and it is used to reflect the overall intensity of water quality response change within the pollution load level range. The preset interval quantity parameter is used to determine the number of pollution load intervals, and its setting process includes the following implementation method: Explanation of the preset interval quantity parameter: After obtaining the pollution load level data, the sample size of the pollution load level data is first determined; based on the sample size, the number of intervals that contain at least multiple effective water quality response change data in each pollution load interval is selected as the preset interval quantity parameter. The preset interval quantity parameter is set to ensure that each pollution load interval has valid samples that can be used to calculate the interval change intensity data, thereby avoiding the impact on the reliability of the water quality response change correlation characteristics due to the interval division being too fine or too coarse. In the specific implementation process, the preset interval quantity parameter can be determined according to one or a combination of the following principles: the number of intervals is determined according to the sample quantity of pollution load level data and the fixed sample capacity requirement, so that each pollution load interval contains no less than the preset number of water quality response change data. Based on the numerical range and sample distribution of pollution load level data, the number of intervals is adjusted to ensure a relatively balanced distribution of water quality response change data within each pollution load interval. The preset interval quantity parameters determined by the above method provide a clear calculation basis and a repeatable implementation path for the pollution load interval division process.

[0027] In this embodiment, by shifting the focus of analysis from the absolute value of a single water quality indicator to the magnitude and intensity of changes in water quality response, the actual impact of pollution load changes on water bodies can be more realistically reflected. Specifically, by performing interpolation processing on water quality response data from adjacent time periods in the pollution load response dataset Lrs, a dataset of water quality response change quantities is formed. This quantifies the rate, magnitude, and direction of water quality changes, avoiding the problem in existing technologies that ignore the trend of change based solely on whether water quality meets standards. Furthermore, by intervalizing the water quality response change quantities according to pollution load levels and calculating the interval change intensity data within different pollution load intervals, a dataset of water quality response change quantities Res is further formed, enabling a stable identification of the correspondence between the intensity of water quality response change and the pollution load level. For example, in actual river monitoring, when water quality indicators are still within the acceptable range but their changes significantly increase in the high pollution load range, traditional methods often fail to identify risks in a timely manner. However, this scheme can directly reflect the characteristics of the intensity of this change amplifying with the increase of pollution load through the water quality response change data set Res, thereby providing a reliable basis for subsequent pollution absorption capacity trend analysis and improving the sensitivity and accuracy of water environment carrying capacity assessment to potential risks.

[0028] Example 4: Specifically: S3 includes S31; S31. Using the water quality response change data set Res as input data, extract the corresponding interval change intensity data in order of pollution load interval from low to high: take the interval change intensity data corresponding to two adjacent pollution load intervals as comparison objects, and obtain the increase data of water quality response change intensity between adjacent pollution load intervals by subtracting the interval change intensity data of the previous pollution load interval from the interval change intensity data of the latter pollution load interval. By repeating the above interval change intensity data for all adjacent pollution load intervals, a data set of water quality response change intensity growth is formed, which is used to represent the change of water quality response change intensity with the increase of pollution load. It should be noted that: The data on the increase in water quality response intensity is a numerical result obtained by calculating the difference between the interval change intensity data corresponding to adjacent pollution load intervals. It is used to represent the incremental change in water quality response intensity as the pollution load increases.

[0029] S3 further includes S32; S32. Based on the data set of water quality response change intensity growth, perform a continuous analysis of the direction of change of the growth data according to the order of pollution load intervals; When the corresponding water quality response change intensity growth data are all greater than zero in multiple consecutive pollution load intervals, and the preset threshold for the number of growth intervals is met, the water quality response change intensity is marked as showing a continuous increasing trend, and it is determined that the pollution absorption capacity of the target water body continues to decrease with the increase of pollution load. When the corresponding water quality response change intensity growth data are all less than zero in multiple consecutive pollution load intervals, and the preset threshold for the number of decreasing intervals is met continuously, the water quality response change intensity is marked as showing a continuous decreasing trend, and it is determined that the target water body's pollution absorption capacity has not continuously decreased with the increase of pollution load. When the increase in water quality response intensity does not continuously meet the threshold for the number of increase intervals or the threshold for the number of decrease intervals, it is marked that the water quality response intensity does not show a unidirectional change trend. It should be noted that: The threshold values ​​for the number of growth intervals and the threshold values ​​for the number of decrease intervals are preset parameters used to determine whether the intensity of water quality response changes shows a continuous trend. Their values ​​are less than the total number of pollution load intervals and are used to ensure that the trend determination is based on the change results of multiple consecutive intervals, rather than the random fluctuations of a single interval. Continuity means that in the ranking of pollution load intervals, the corresponding water quality response change intensity growth data of multiple adjacent intervals are consistent in the direction of change, thereby ensuring that the trend judgment has continuity in time or pollution load evolution; Explanation regarding the state of no clear trend: When the increase in the intensity of water quality response changes alternates between different pollution load intervals and does not continuously meet the threshold for the number of increasing intervals or the threshold for the number of decreasing intervals, it is determined to be a state of no clear trend. This is to avoid misjudging random fluctuations as a trend of changes in pollution absorption capacity.

[0030] S3 also includes S33; S33. Based on the number of intervals that satisfy the continuous increasing trend and the continuous decreasing trend respectively in the data set of water quality response change intensity growth, and their distribution in the overall pollution load interval, perform trend summary processing to distinguish the direction of the interval growth data of continuous increasing trend and continuous decreasing trend, obtain trend result data, and form trend result data to represent the overall change direction and degree of water quality response change intensity. The trend results data are output as the pollution absorption saturation trend index, Sat. Among them, the pollution absorption saturation trend index Sat is a trend index that comprehensively reflects both the increasing and decreasing trend contributions of the water quality response intensity. Among them, when the intensity of water quality response changes shows a continuous increasing trend, the value of the pollution absorption saturation trend index Sat increases linearly with the increase of the number of intervals that continuously meet the threshold of the number of growth intervals, which is used to indicate that the pollution absorption capacity of the target water body gradually approaches the saturation state as the pollution load increases. When the intensity of water quality response changes shows a continuous decreasing trend, the value of the pollution absorption saturation trend index Sat decreases linearly as the number of intervals that continuously meet the threshold of decreasing intervals increases. This is used to indicate that the pollution absorption capacity of the target water body is in a relatively stable or improved state as the pollution load increases.

[0031] In this embodiment, by constructing a dataset of the increase in water quality response intensity and performing continuous analysis on the direction of increase within adjacent pollution load intervals, it is possible to effectively distinguish whether the water quality response change is caused by occasional fluctuations or is the result of continuous amplification during the increase in pollution load. This avoids the risk of misjudging the deterioration of water body carrying capacity based solely on a single change or local anomaly in existing technologies. Furthermore, by summarizing and processing the number and distribution of intervals that satisfy continuous increasing and decreasing trends, a pollution absorption saturation trend index, Sat, is formed. This transforms the process of pollution absorption capacity approaching saturation from "post-event observation of water quality deterioration" to "early identification of changing trends." For example, in actual lakes or slow-flowing river sections, when the pollution load gradually increases but the water quality indicators have not yet significantly exceeded the standards, traditional assessment methods often assume that the water body still has a carrying capacity. However, by using the pollution absorption saturation trend index Sat, it can be found that the intensity of water quality response changes continues to increase in the high pollution load range, thereby indicating in advance that the pollution absorption capacity of the target water body is rapidly declining. This provides a basis for management departments to take emission restriction or control measures before the water quality is out of control, and significantly improves the ability of water environment carrying capacity assessment to identify "near saturation state".

[0032] Example 5: Specifically: S4 includes S41; S41. Based on the existing water environment assessment system, assess the current state of the target water body to obtain the benchmark bearing capacity state result used to represent the basic bearing condition of the target water body; The baseline bearing capacity state results are used as a reference basis for subsequent bearing capacity correction processing; The pollution absorption saturation trend index Sat is compared with the trend determination criteria used to determine the continuous increasing trend and the continuous decreasing trend. Based on the comparison results, the baseline carrying capacity state results are corrected to obtain the corrected water environment carrying capacity state. When the pollution absorption saturation trend index Sat meets the judgment condition corresponding to the continuous increase trend, it is determined that the pollution absorption capacity of the target water body is in a declining state, and the benchmark carrying capacity state result is linearly negatively corrected to reduce the carrying capacity judgment level of the target water body. When the pollution absorption saturation trend index Sat meets the judgment condition corresponding to the continuous decreasing trend, it is determined that the pollution absorption capacity of the target water body is in a relatively stable or improved state, and the benchmark carrying capacity state result is linearly positively corrected. When the pollution absorption saturation trend index Sat does not meet the judgment conditions of continuous increase or continuous decrease, the baseline carrying capacity state result remains unchanged and is used as the corresponding corrected water environment carrying capacity state. It should be noted that: The negative correction refers to the process of downgrading the baseline carrying capacity status result or upgrading the risk level when the pollution absorption saturation trend index Sat indicates a continuous decline in pollution absorption capacity. The positive correction refers to the process of maintaining the baseline carrying capacity status or downgrading the risk level when the pollution absorption saturation trend index Sat indicates that the pollution absorption capacity is stable or improving.

[0033] S4 also includes S42; S42. Based on the obtained corrected water environment carrying capacity status as the judgment basis, and the correspondence between it and the preset carrying risk judgment conditions, the target water body is divided into the corresponding carrying risk level. The risk levels are categorized into low-risk, medium-risk, and high-risk levels. When the modified water environment carrying capacity status falls within the judgment range corresponding to the low-risk carrying capacity level, the target water body is classified as a low-risk carrying capacity level. When the modified water environment carrying capacity status falls within the judgment range corresponding to the medium-risk carrying capacity level, the target water body will be classified as a medium-risk carrying capacity level. When the modified water environment carrying capacity status falls within the judgment range corresponding to the high-risk carrying capacity level, the target water body will be classified as a high-risk carrying capacity level. The identification information of the target water body, the corresponding corrected water environment carrying capacity status, and the determined carrying capacity risk level are collected as early warning output results to generate a carrying capacity early warning result set War; Among them, the carrying capacity early warning result set War is used to represent the water environment carrying risk status that the target water body may face under the influence of the changing trend of pollution absorption capacity; It should be noted that: The risk assessment criteria are a set of assessment rules used to map the corrected water environment carrying capacity state to different risk levels. The risk assessment criteria are set based on the relative level of the carrying capacity status and the direction of carrying capacity change, in order to avoid risk assessment based solely on a single carrying capacity result. In practice, the risk assessment criteria include at least one or a combination of the following dimensions: The positional relationship between the corrected water environment carrying capacity state and the preset safe carrying capacity range; The direction and magnitude of the change in the corrected water environment carrying capacity state relative to the baseline carrying capacity state; The scope of load-bearing risk assessment can be set as follows: When the corrected water environment carrying capacity status is within the preset safe range of carrying capacity, and there is no adjustment towards a high-risk direction relative to the benchmark carrying capacity status result, the target water body is classified as a low-risk carrying capacity level. When the corrected water environment carrying capacity status is close to the boundary of the preset carrying capacity safe range, or when the result of the benchmark carrying capacity status has been adjusted once towards a high-risk direction, the target water body will be classified as a medium-risk carrying capacity level. When the corrected water environment carrying capacity status exceeds the preset safe range of carrying capacity, or when there have been multiple consecutive adjustments towards high risk relative to the benchmark carrying capacity status, the target water body will be classified as a high-risk carrying capacity level.

[0034] In this embodiment, by comparing the pollution absorption saturation trend index (Sat) with the trend judgment conditions, a linear negative or linear positive correction is applied to the baseline carrying capacity status result. This allows for the early downgrading of the target water body's carrying capacity judgment level even when water quality has not significantly deteriorated but pollution absorption capacity has been continuously declining. This addresses the problem in existing technologies where carrying capacity assessment results lag behind actual risk changes. Based on this, and by combining the corrected water environment carrying capacity status with preset carrying capacity risk judgment conditions, the target water body is classified into low-risk, medium-risk, or high-risk carrying capacity levels, and a carrying capacity early warning result set (War) is generated. This allows for the intuitive output of water environment carrying capacity risk in the form of tiered early warnings. For example, in actual watershed management, when the baseline carrying capacity of a certain river section is still within the safe range, but a linear negative correction is triggered due to the continuous increase of the pollution absorption saturation trend index Sat, this method can adjust the river section from a low-risk carrying capacity level to a medium-risk carrying capacity level. It can also indicate the potential risk increase through the carrying capacity early warning result set War, thereby providing a decision-making basis for management departments to implement discharge restriction, regulation, or diversion measures before the pollution load exceeds the carrying capacity limit. This significantly improves the guiding value and early warning practicality of the water environment carrying capacity assessment results in actual management.

[0035] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended technical solutions and their equivalents.

Claims

1. A method for assessing and analyzing the carrying capacity of water environment, characterized in that: Includes the following steps: S1. Collect pollution load data of the target water body during the historical operating cycle and water quality response data corresponding to the pollution load data, and integrate the pollution load data and the water quality response data based on the time correspondence to generate a pollution load response data set Lrs; S2. Analyze the pollution load response data set Lrs to obtain the characteristic information of water quality response changing with pollution load, and generate a water quality response change data set Res based on the characteristic information; S3. Based on the water quality response change data set Res, calculate the trend information of the target water body's pollution absorption capacity with the change of pollution load, and obtain the pollution absorption saturation trend index Sat. S4. Introduce the pollution absorption saturation trend index Sat into the water environment carrying capacity assessment process to correct the water environment carrying capacity assessment results, and generate a carrying capacity early warning result set War based on the corrected water environment carrying capacity status.

2. The water environment carrying capacity assessment and early warning analysis method according to claim 1, characterized in that: S1 includes S11; S11. Taking the target water body as the object, the historical operating cycle is divided into multiple consecutive time periods according to the preset historical operating cycle; Within each time period, the corresponding pollution load data and the water quality response data that are time-matched with the pollution load data are acquired respectively; The pollution load data is used to reflect the input of pollutants into the target water body during the time period. The water quality response data is used to reflect the water quality changes of the target water body caused by the input of the pollutants during the time period. The data are then integrated to form a set of raw pollution load data arranged by time period and a set of raw water quality response data.

3. The water environment carrying capacity assessment and early warning analysis method according to claim 2, characterized in that: S1 further includes S12; S12. Based on the original pollution load data set and the original water quality response data set, the pollution load data and water quality response data within the same time period are paired according to the time period correspondence. After pairing, the pollution load data and water quality response data corresponding to each time group are integrated to generate a data unit containing pollution load information and corresponding water quality response information. The multiple data units are aggregated in chronological order to form a pollution load response data set Lrs.

4. The water environment carrying capacity assessment and early warning analysis method according to claim 3, characterized in that: S2 includes S21; S21. Using the pollution load response dataset Lrs as input data, process the data unit corresponding to each time period in sequence to construct the basic data of water quality response change for subsequent analysis. The process specifically includes steps S211, S212, and S213; S211. The pollution load data recorded in the data unit is summed up for all pollutant inputs during the time period to obtain pollution load level data representing the overall pollutant input intensity during the time period. S212. For the water quality response data recorded in the data unit, the average value of multiple water quality monitoring results obtained within the time period is calculated to obtain water quality response numerical data that represents the overall water quality status of the water body during the time period. S213. Using the data units corresponding to two adjacent time periods as comparison objects, the water quality response numerical data in adjacent time periods are processed by difference to obtain the change results of water quality response between adjacent time periods, thereby forming water quality response change data. By repeating the above processing procedure on all adjacent data units in the pollution load response dataset Lrs, a dataset of water quality response change is formed.

5. The water environment carrying capacity assessment and early warning analysis method according to claim 4, characterized in that: S2 further includes S22; S22. Based on the data set of water quality response changes, execute steps S221, S222 and S223 to extract the correlation features between water quality response changes and pollution load changes. S221. Based on all the obtained pollution load level data, first obtain the minimum and maximum values ​​in the pollution load level data to determine the overall numerical range of pollution load changes. Within the overall numerical range, the overall numerical range is divided into multiple consecutive pollution load intervals according to a preset interval number parameter; Each pollution load interval corresponds to a specific pollution load value range, which is used to collect water quality response change data where the pollution load level falls within that value range. S222. For each pollution load interval, extract all water quality response change data that fall within that pollution load interval. The average value of the water quality response change data is calculated to obtain the interval change intensity data representing the intensity of water quality response change within the pollution load interval; S223. Arrange and aggregate the interval change intensity data corresponding to different pollution load intervals in order of pollution load interval from low to high to form a water quality response change data set Res.

6. The water environment carrying capacity assessment and early warning analysis method according to claim 5, characterized in that: S3 includes S31; S31. Using the water quality response change data set Res as input data, extract the corresponding interval change intensity data in order of pollution load interval from low to high: take the interval change intensity data corresponding to two adjacent pollution load intervals as comparison objects, and obtain the increase data of water quality response change intensity between adjacent pollution load intervals by subtracting the interval change intensity data of the previous pollution load interval from the interval change intensity data of the latter pollution load interval. By repeating the above interval change intensity data for all adjacent pollution load intervals, a data set of water quality response change intensity growth is formed.

7. The method for assessing and early warning analysis of water environment carrying capacity according to claim 6, characterized in that: S3 further includes S32; S32. Based on the data set of water quality response change intensity growth, perform a continuous analysis of the direction of change of the growth data according to the order of pollution load intervals; When the corresponding water quality response change intensity growth data are all greater than zero in multiple consecutive pollution load intervals, and the preset threshold for the number of growth intervals is met, the water quality response change intensity is marked as showing a continuous increasing trend, and it is determined that the pollution absorption capacity of the target water body continues to decrease with the increase of pollution load. When the corresponding water quality response change intensity growth data are all less than zero in multiple consecutive pollution load intervals, and the preset threshold for the number of decreasing intervals is met continuously, the water quality response change intensity is marked as showing a continuous decreasing trend, and it is determined that the target water body's pollution absorption capacity has not continuously decreased with the increase of pollution load. When the increase in water quality response intensity does not continuously meet the threshold for the number of increase intervals or the threshold for the number of decrease intervals, it is marked that the water quality response intensity does not show a unidirectional change trend.

8. The water environment carrying capacity assessment and early warning analysis method according to claim 7, characterized in that: S3 also includes S33; S33. Based on the number of intervals that satisfy the continuous increasing trend and the continuous decreasing trend respectively in the data set of water quality response change intensity growth, and their distribution in the overall pollution load interval, perform trend summary processing to distinguish the direction of the interval growth data of continuous increasing trend and continuous decreasing trend, and obtain trend result data. The trend results data are output as the pollution absorption saturation trend index, Sat. Among them, the pollution absorption saturation trend index Sat is a trend index that comprehensively reflects both the increasing and decreasing trend contributions of the water quality response intensity.

9. The water environment carrying capacity assessment and early warning analysis method according to claim 8, characterized in that: S4 includes S41; S41. Based on the existing water environment assessment system, assess the current state of the target water body to obtain the benchmark bearing capacity state result used to represent the basic bearing condition of the target water body; The baseline bearing capacity state results are used as a reference basis for subsequent bearing capacity correction processing; The pollution absorption saturation trend index Sat is compared with the trend determination criteria used to determine the continuous increasing trend and the continuous decreasing trend. Based on the comparison results, the baseline carrying capacity state results are corrected to obtain the corrected water environment carrying capacity state. When the pollution absorption saturation trend index Sat meets the judgment condition corresponding to the continuous increase trend, it is determined that the pollution absorption capacity of the target water body is in a declining state, and the benchmark carrying capacity state result is linearly negatively corrected to reduce the carrying capacity judgment level of the target water body. When the pollution absorption saturation trend index Sat meets the judgment condition corresponding to the continuous decreasing trend, it is determined that the pollution absorption capacity of the target water body is in a relatively stable or improved state, and the benchmark carrying capacity state result is linearly positively corrected. When the pollution absorption saturation trend index Sat does not meet the judgment conditions of continuous increase or continuous decrease, the baseline carrying capacity state result remains unchanged and is used as the corresponding corrected water environment carrying capacity state.

10. The method for assessing and early warning analysis of water environment carrying capacity according to claim 9, characterized in that: S4 also includes S42; S42. Based on the obtained corrected water environment carrying capacity status as the judgment basis, and the correspondence between it and the preset carrying risk judgment conditions, the target water body is divided into the corresponding carrying risk level. The risk levels include low-risk, medium-risk, and high-risk levels. When the modified water environment carrying capacity status falls within the judgment range corresponding to the low-risk carrying capacity level, the target water body is classified as a low-risk carrying capacity level. When the modified water environment carrying capacity status falls within the judgment range corresponding to the medium-risk carrying capacity level, the target water body will be classified as a medium-risk carrying capacity level. When the modified water environment carrying capacity status falls within the judgment range corresponding to the high-risk carrying capacity level, the target water body will be classified as a high-risk carrying capacity level. The identification information of the target water body, the corresponding corrected water environment carrying capacity status, and the determined carrying capacity risk level are collected as early warning output results to generate a carrying capacity early warning result set War.

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