Water quality detection and evaluation method and system for environmental engineering

Abstract

The invention discloses a water quality detection and evaluation method and system for environmental engineering, and relates to the technical field of environmental engineering. The method comprises the following steps: collecting and detecting an environmental engineering target water sample to obtain concentration data of various pollutants; constructing a pollutant collaborative influence matrix, calculating a collaborative index of the influence of each pollutant on the overall water quality, and generating a comprehensive pollution collaborative score; obtaining a water body function type of the target water sample, performing water body function matching judgment on the target water sample, and outputting a function adaptability grade; collecting a pollutant concentration change sequence in a historical period of time, and performing time sequence analysis on the concentration of each pollutant to obtain a predicted pollution trend; and dynamically adjusting the comprehensive pollution collaborative score and the functional adaptability grade to obtain a dynamic standard evaluation result of the target water sample. According to the method, comprehensive dynamic evaluation on the pollution status, functional adaptability and future trend of the target water sample is realized, and the scientificity and timeliness of water quality evaluation are remarkably improved.

Description

Technical Field

[0001] The present application relates to the field of environmental engineering technology, and in particular to a method and system for detecting and evaluating water quality in environmental engineering. Background Art

[0002] Water quality testing and assessment is one of the core technologies to ensure water resource security and ecological health. It is widely used in multiple scenarios such as surface water, groundwater, drinking water sources, sewage treatment and discharge. By detecting and analyzing the types and concentrations of pollutants in water bodies, the pollution status and environmental quality level of water bodies can be fully understood, providing key data support and decision-making basis for water resource management, pollution prevention and control, ecological protection and engineering governance, thereby achieving precise control and sustainable utilization of the water environment, and promoting scientific and refined management of environmental engineering.

[0003] In related technologies, commonly used environmental engineering water quality testing and assessment methods usually focus on detecting the concentration of a single pollutant or a limited number of pollutants, and make simple exceedance judgments based on fixed thresholds. This makes it difficult to fully reflect the synergistic effects of multiple pollutants and their combined impact on water body functions. At the same time, there is a lack of modeling and prediction of the dynamic changes in water pollution conditions. The assessment results are often static and isolated, unable to effectively adapt to the diverse requirements of different water body functional types, and unable to dynamically adjust the assessment standards to match actual environmental changes. This leads to problems such as one-sidedness, lags, and lack of adaptability in the assessment results, making it difficult to provide a highly reliable decision-making basis for environmental governance and water resources regulation. There is room for improvement. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for water quality detection and evaluation in environmental engineering to solve the problems raised in the above background technology.

[0005] In the first aspect, the present application provides a method for water quality detection and assessment in environmental engineering, which adopts the following technical solution:

[0006] Collect target water samples for environmental engineering, conduct pollutant detection on the pre-treated target water samples, and obtain concentration data of various pollutants in the target water samples;

[0007] Based on the concentration data of multiple pollutants, a pollutant synergistic impact matrix is ​​constructed to calculate the synergistic index of each pollutant's impact on the overall water quality and generate a comprehensive pollution synergy score;

[0008] Obtain the water body function type of the target water sample, set a pollutant index set and threshold system for each type of water body function, perform water body function matching judgment on the target water sample, and output the functional adaptability level;

[0009] Collect the pollutant concentration change series of the water body to be evaluated over the historical period, conduct time series analysis on the concentration of each pollutant, and obtain the predicted pollution trend;

[0010] Based on the predicted pollution trend, the comprehensive pollution synergy score and the functional adaptability level are dynamically adjusted to obtain a dynamic standard assessment result of the target water sample.

[0011] Preferably, the steps of collecting target water samples for environmental engineering, performing pollutant detection on the pretreated target water samples, and obtaining concentration data of multiple pollutants in the target water samples are specifically as follows:

[0012] Collecting target water samples for environmental engineering and pre-treating the target water samples;

[0013] According to the characteristics and properties of water pollution in environmental projects, set the pollutant items that need to be tested and select the corresponding testing methods for each pollutant;

[0014] According to the detection method, the concentration of various pollutants in the pretreated target water sample is detected to obtain concentration data of multiple pollutants in the target water sample.

[0015] Preferably, based on the concentration data of multiple pollutants, a pollutant synergistic impact matrix is ​​constructed, the synergistic index of the impact of each pollutant on the overall water quality is calculated, and the steps of generating a comprehensive pollution synergy score are specifically as follows:

[0016] Based on the concentration data of various pollutants, the concentrations of various pollutants are normalized to obtain the standardized pollutant concentration vector;

[0017] Based on the interaction mechanism between pollutants, a pollutant synergistic impact matrix is ​​constructed, wherein the synergistic impact matrix is ​​used to represent the synergistic relationship between any two pollutants in affecting water quality;

[0018] Based on the standardized pollutant concentration vector and the pollutant synergistic impact matrix, the synergistic index of each pollutant's impact on the overall water quality is calculated to generate a comprehensive pollution synergy score.

[0019] Preferably, the steps of constructing a pollutant synergistic impact matrix based on the interaction mechanism between pollutants are as follows:

[0020] Extracting pollutant types from the target water sample and constructing a pollutant type set;

[0021] Based on historical water sample data, the interaction information between each pair of pollutants is counted to establish a pollutant interaction factor library;

[0022] Based on the pollutant interaction factor library, obtaining the synergistic effect type and synergistic effect intensity between each pair of pollutants;

[0023] According to the synergistic effect type and synergistic effect intensity, synergistic impact factors are set for any two pollutants in the pollutant type set to generate a pollutant synergistic impact matrix.

[0024] Preferably, the step of calculating the synergy index of the impact of each pollutant on the overall water quality based on the standardized pollutant concentration vector and the pollutant synergy impact matrix and generating a comprehensive pollution synergy score is specifically as follows:

[0025] Based on the standardized pollutant concentration vector and the pollutant synergistic influence matrix, performing a matrix operation on the standardized pollutant concentration vector and the pollutant synergistic influence matrix to obtain a pollutant synergistic index vector;

[0026] Based on the pollutant synergy index vector, a pollutant weight vector is obtained, and the pollutant synergy index vector and the pollutant weight vector are weighted and aggregated to generate a comprehensive pollution synergy score of the target water sample.

[0027] Preferably, the steps of obtaining the water function type of the target water sample, setting a pollutant index set and a threshold system for each type of water function, performing water function matching determination on the target water sample, and outputting the function adaptability level are specifically as follows:

[0028] Obtaining environmental background information of the target water sample, and identifying the corresponding water body function type based on the environmental background information;

[0029] Based on the water body function type, a corresponding pollutant index set is set for each type of water body function, and a concentration threshold value corresponding to the water body function level is set for each pollutant index;

[0030] Extracting the concentration data of various pollutants in the target water sample, and matching and judging the concentrations of various pollutants with the concentration thresholds in the pollutant index set;

[0031] Based on the degree of matching between the pollutant concentration and the concentration threshold, the matching score of the target water sample under the current water body function is calculated, and the functional adaptability level is output.

[0032] Preferably, the steps of collecting the pollutant concentration change sequence of the water body to be evaluated in the historical period, performing time series analysis on the concentration of each pollutant, and obtaining the predicted pollution trend are specifically as follows:

[0033] Obtain pollutant concentration monitoring data of the water body to be assessed at different historical periods and construct a pollutant concentration time series vector;

[0034] Performing missing value repair and data smoothing processing on the pollutant concentration time series vector to form time series characteristic data of pollutant concentration;

[0035] Based on the time series characteristic data, a pollution trend analysis model is constructed using a time series analysis method;

[0036] Based on the pollution trend analysis model and the concentration data of multiple pollutants in the target water sample, the concentration change trend of each pollutant in the future time period is predicted to obtain the predicted pollution trend.

[0037] Preferably, based on the predicted pollution trend, the comprehensive pollution synergy score and the functional adaptability level are dynamically adjusted to obtain the dynamic standard evaluation result of the target water sample, specifically:

[0038] Based on the predicted pollution trend, dynamically adjusting the synergy index in the pollutant synergy impact matrix;

[0039] If the predicted concentration of a pollutant increases, the synergy index of the pollutant in the pollutant synergy impact matrix is ​​amplified accordingly;

[0040] If the predicted concentration of a pollutant decreases, the synergy index of the pollutant in the pollutant synergy impact matrix will be reduced accordingly;

[0041] Combining the dynamically adjusted pollutant synergistic impact matrix and the standardized pollutant concentration vector of the target water sample, the comprehensive pollution synergistic score is calculated again to generate a predicted pollution synergistic score;

[0042] Dynamically adjusting the functional adaptability level based on the predicted pollution trend;

[0043] If the predicted pollutant concentration exceeds the pollutant index concentration threshold corresponding to a certain water body function, the functional adaptability level of the target water sample under the water body function is reduced to generate a predicted functional adaptability level;

[0044] The predicted pollution collaborative score and the predicted functional adaptability level are integrated to output a dynamic standard evaluation result of the target water sample.

[0045] In a second aspect, the present application provides a water quality detection and evaluation system for environmental engineering, which adopts the following technical solutions:

[0046] A water quality detection and evaluation system for environmental engineering, comprising:

[0047] The pollution detection module collects target water samples for environmental engineering, performs pollutant detection on the pre-treated target water samples, and obtains the concentration data of various pollutants in the target water samples;

[0048] The collaborative analysis module constructs a pollutant synergistic impact matrix based on multiple pollutant concentration data, calculates the synergistic index of each pollutant's impact on overall water quality, and generates a comprehensive pollution synergy score;

[0049] Functional assessment module: obtains the water function type of the target water sample, sets a pollutant index set and threshold system for each type of water function, makes a water function matching judgment for the target water sample, and outputs the functional adaptability level;

[0050] The trend prediction module collects the pollutant concentration change sequence of the water body to be evaluated over the historical period, performs time series analysis on the concentration of each pollutant, and obtains the predicted pollution trend;

[0051] The dynamic adjustment module dynamically adjusts the comprehensive pollution synergy score and the functional adaptability level based on the predicted pollution trend to obtain a dynamic standard evaluation result of the target water sample.

[0052] In summary, this application includes at least one of the following beneficial technical effects:

[0053] 1. Pretreatment of target water samples and collection of data on multiple pollutant concentrations ensure comprehensive and accurate test results. A synergistic impact matrix, based on the synergistic impact relationships between pollutants, is constructed to reveal amplification or offsetting effects between pollutants. The synergy index quantifies the extent of this impact and calculates the synergy index of each pollutant on overall water quality, generating a more scientific and reasonable pollution synergy score, providing a more scientific evaluation indicator for pollution severity. Furthermore, the functional adaptability of water samples is assessed based on the pollutant indicators and threshold systems required for each function, taking into account the functional type of the water body. This allows for differentiated and targeted assessment standards, enhancing the pertinence and practicality of the assessment. Historical data sequence analysis is further introduced to predict pollutant concentration trends and provide a trend assessment of future water quality states. This contributes to a dual evaluation mechanism combining static detection and dynamic prediction, improving the foresight and adaptability of the assessment system. Finally, through a dynamic adjustment mechanism, trend prediction results are fed back into the assessment model, adaptively modifying the pollution synergy score and functional adaptability level, producing dynamic standard assessment results that are more timely, forward-looking, and valuable for decision-making, effectively improving the scientific nature, accuracy, and practical value of environmental water sample assessments.

[0054] 2. In actual water samples, the concentration ranges and units of different pollutants may vary greatly. Directly using raw data for collaborative analysis can easily lead to calculation bias. Normalization eliminates this dimensional interference, so that pollutants have the same analytical weight in the mathematical model, improving the scientificity and rationality of data fusion processing. In reality, water pollution is often the result of the combined effects of multiple pollutants. The impact assessment of a single pollutant cannot fully reflect the pollution situation. By constructing a pollutant synergistic impact matrix, the positive or negative correlation between pollutants can be revealed, the multi-factor perception ability of the assessment model can be improved, and the water quality risk assessment is closer to reality. Through matrix operations, the actual concentration performance of pollutants and their interactive influence relationships are fused and calculated to obtain a synergistic index reflecting the overall pollution level, and then form a quantitative scoring result for the water quality of the target water sample. The comprehensive pollution synergistic score not only reflects the individual concentration status of each pollutant, but also introduces the weight adjustment of the synergistic effect. It can accurately assess the comprehensive pollution load of the water body and provide a unified standard criterion and analysis starting point for subsequent water function adaptability analysis and pollution trend prediction.

[0055] 3. Pollutants do not exhibit static synergies. Future concentration trends will directly influence the strength of their synergistic effects. Dynamic adjustments to the synergy index in the pollutant synergy impact matrix allow for dynamic changes in pollutant interactions over time and trends. This improves the timeliness and foresight of the assessment model, ensuring that synergies reflect the latest anticipated pollution patterns rather than static historical states, thereby avoiding lags in assessment results. By scaling the synergy index up or down, the weight of concentration trends on the overall pollution synergy is reflected, highlighting the dynamic contribution of pollutants to the system's potential risk. Recalculating the pollution synergy score reflects dynamic changes in potential risk levels, providing a predictive supplement to the original static score. This improves the time sensitivity and strategic foresight of the assessment and enables a reassessment of pollution synergy risks under future pollution scenarios. Because future pollution deterioration may render currently adapted functions unsafe or unsuitable, dynamic intervention and adjustment of the functional adaptability level is necessary. Incorporating pollution trend information into the water body function assessment system avoids judging functional adaptability based solely on current conditions and helps identify potential risk points of non-adaptability to water body functions. By comparing water quality with functional thresholds, it can identify in advance when water quality will no longer meet certain usage requirements, allowing for appropriate adjustments to the functional adaptability level and proactive early warning of water function management. By integrating the two dimensions of pollution synergy intensity and functional adaptability, a dynamic assessment results for the future state is provided, enhancing responsiveness to changing pollution risks and foresight in functional matching judgments, significantly improving the intelligent and scientific nature of water management and risk warnings. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1It is a schematic diagram of the specific steps of an embodiment of a method for detecting and evaluating water quality in environmental engineering according to the present invention.

[0057] Figure 2 This is a schematic diagram of module connections in an embodiment of a water quality detection and evaluation system for environmental engineering according to the present invention. DETAILED DESCRIPTION

[0058] Below is a combination of the embodiments and Figure 1-Figure 2 The present invention will be described in further detail, but the embodiments of the present invention are not limited thereto.

[0059] The present invention discloses a method for detecting and evaluating water quality in environmental engineering, which specifically comprises the following steps:

[0060] Step S1: Collect target water samples for environmental engineering, perform pollutant detection on the pre-treated target water samples, and obtain concentration data of multiple pollutants in the target water samples;

[0061] Step S2: Based on the concentration data of multiple pollutants, a pollutant synergistic impact matrix is ​​constructed to calculate the synergistic index of each pollutant's impact on the overall water quality and generate a comprehensive pollution synergy score;

[0062] Step S3: Obtain the water function type of the target water sample, set a pollutant index set and threshold system for each type of water function, perform water function matching judgment on the target water sample, and output the function adaptability level;

[0063] Step S4: collecting pollutant concentration change sequences of the water body to be evaluated over historical periods, performing time series analysis on the concentrations of each pollutant, and obtaining a predicted pollution trend;

[0064] Step S5: Based on the predicted pollution trend, the comprehensive pollution synergy score and the functional adaptability level are dynamically adjusted to obtain a dynamic standard evaluation result of the target water sample.

[0065] In practical applications, collecting and pre-treating water samples can remove or control interfering factors such as suspended particles and pH abnormalities, ensuring the objectivity and representativeness of pollutant detection data. This provides fundamental input for subsequent modules such as pollution synergy analysis and functional matching determination, forming a key source of raw data for the entire assessment system. The construction of a synergistic impact matrix can reveal amplification or offsetting effects between pollutants. The synergy index quantifies the extent of this influence, and then calculates a comprehensive pollution synergy score, providing a more scientific assessment indicator of pollution severity. By constructing a pollutant indicator set and a functional threshold system, the assessment criteria are differentiated and targeted, making the results more practical. The functional adaptability level reflects the carrying capacity of water samples for different water uses and is an important reference for environmental engineering management and planning. By introducing a time dimension, dynamic modeling of pollutant changes is performed to reveal their potential development trends and rates of change. Time series analysis can predict future pollution trends, helping to implement a dual evaluation mechanism combining static detection and dynamic prediction, improving the foresight and adaptability of the assessment system. The prediction results are fed back to the core evaluation indicators, and the original evaluation results are dynamically revised in combination with the current detection values ​​and future pollution trends. Through the dynamic adjustment mechanism, the possible deterioration or improvement trends of water quality can be reflected, making the final evaluation results time-sensitive and strategically valuable, providing a scientific basis for the formulation of long-term governance strategies and dynamic water resource allocation.

[0066] The steps of collecting target water samples for environmental engineering, testing the pretreated target water samples for pollutants, and obtaining concentration data of multiple pollutants in the target water samples are as follows:

[0067] Step S11, collecting target water samples for environmental engineering and pre-processing the target water samples;

[0068] Step S12: According to the characteristics and properties of water pollution in environmental projects, the pollutant items to be tested are set, and the corresponding detection method is selected for each pollutant;

[0069] Step S13: According to the detection method, the concentration of various pollutants in the pretreated target water sample is detected to obtain concentration data of multiple pollutants in the target water sample.

[0070] In practical application, collecting target water samples through scientific and standardized methods and pre-treating them, such as filtration, acidification, and constant temperature storage, can eliminate interfering substances, inhibit microbial activity, and prevent fluctuations in pollutant concentrations. This provides a stable and reliable sample base for subsequent accurate testing and helps to restore the original pollution characteristics of the water body to the greatest extent possible. Different water bodies in environmental engineering have different functions and pollution characteristics. Therefore, it is necessary to rationally define pollutant items, such as heavy metals, organic matter, nitrogen and phosphorus, according to industry standards to ensure that key factors that may affect water functions are tested. Furthermore, selecting a detection method that is technically appropriate, highly sensitive, and has low error for each pollutant, such as atomic absorption spectroscopy, ion chromatography, and high-performance liquid chromatography, can significantly improve the accuracy and reproducibility of test data, providing high-quality raw data for subsequent synergistic scoring and trend prediction. By testing pollutant concentrations in pre-treated water samples, the actual concentrations of various pollutants in the water sample can be fully understood, providing direct data support for the subsequent construction of the pollutant synergistic impact matrix and functional adaptability assessment, significantly enhancing the scientific nature and rigorous execution logic of the entire assessment system.

[0071] Based on the concentration data of multiple pollutants, the pollutant synergistic impact matrix is ​​constructed, the synergistic index of each pollutant's impact on the overall water quality is calculated, and the steps to generate a comprehensive pollution synergy score are as follows:

[0072] Step S21: Based on the multiple pollutant concentration data, normalize the concentrations of various pollutants to obtain a standardized pollutant concentration vector;

[0073] Step S22: constructing a pollutant synergistic impact matrix based on the interaction mechanism between pollutants. The synergistic impact matrix is ​​used to represent the synergistic relationship between any two pollutants in affecting water quality.

[0074] Step S23 , based on the standardized pollutant concentration vector and the pollutant synergistic impact matrix, calculate the synergistic index of each pollutant's impact on the overall water quality and generate a comprehensive pollution synergy score.

[0075] In practical applications, the concentration ranges and units of different pollutants in real water samples can vary significantly. Directly using raw data for synergistic analysis can easily lead to computational bias. Normalization eliminates this dimensionality interference, ensuring that pollutants have equal analytical weights in the mathematical model, thus improving the scientific and rationality of data fusion processing. Real-world water pollution often results from the combined effects of multiple pollutants. The impact assessment of a single pollutant cannot fully reflect the pollution situation. By constructing a pollutant synergistic impact matrix, it can reveal positive correlations (synergistic enhancement) or negative correlations (mutual cancellation) between pollutants, enhancing the multi-factor perception of the assessment model and making water quality risk assessment more realistic. Through matrix operations, the actual concentrations of pollutants are combined with their interactions to produce a synergistic index reflecting the overall pollution level, which in turn forms a quantitative score for the target water sample. The comprehensive pollution synergistic score not only reflects the individual concentrations of each pollutant but also incorporates synergistic weighting. This accurately assesses the overall pollution load of a water body, providing a unified standard and analytical starting point for subsequent water function adaptability analysis and pollution trend prediction.

[0076] According to the interaction mechanism between pollutants, the steps to construct the pollutant synergistic impact matrix are as follows:

[0077] Step S221, extracting pollutant types in the target water sample and constructing a pollutant type set;

[0078] Step S222: Based on historical water sample data, statistics are collected on the interaction information between each pair of pollutants to establish a pollutant interaction factor library;

[0079] Step S223: obtaining the synergistic effect type and synergistic effect intensity between each pair of pollutants based on the pollutant interaction factor library;

[0080] Step S224 : According to the synergistic effect type and synergistic effect strength, a synergistic effect factor is set for any two pollutants in the pollutant type set to generate a pollutant synergistic effect matrix.

[0081] In practical applications, by extracting pollutant types and constructing sets to identify the pollutant components present in the target water sample, the boundaries and targets of pollution analysis can be defined, preventing irrelevant or redundant information from interfering with calculations, and thus improving the relevance and accuracy of pollution synergy modeling. By mining a large amount of existing historical water sample data, the synergistic or antagonistic relationships between different pollutants in real environments can be analyzed, providing a data basis for pollutant synergy modeling. Constructing an interaction factor library can summarize the interaction patterns of common pollutant combinations, enhancing the empirical and practical applicability of the model while also supporting the subsequent construction of the synergistic impact matrix. Building on the statistical data from the previous step, the synergistic impact relationships between pollutants are further refined, defining specific interaction types such as synergistic enhancement, neutral independence, or synergistic weakening, and quantifying their intensity, making the pollutant synergy mechanisms calculable and distinguishable. Transforming the complex interactions between pollutants into a structured, numerical synergistic impact matrix, in which each element represents the degree of synergistic impact between two pollutant types, provides a quantitative basis for calculating the comprehensive pollution synergy score. Linking pollution data with scoring logic is a key step in achieving intelligent and systematic pollution assessment models.

[0082] The steps of calculating the synergy index of each pollutant's impact on the overall water quality based on the standardized pollutant concentration vector and the pollutant synergy impact matrix and generating a comprehensive pollution synergy score are as follows:

[0083] Step S231 , based on the standardized pollutant concentration vector and the pollutant synergistic influence matrix, performing a matrix operation on the standardized pollutant concentration vector and the pollutant synergistic influence matrix to obtain a pollutant synergistic index vector;

[0084] Step S232: Based on the pollutant synergy index vector, a pollutant weight vector is obtained, and the pollutant synergy index vector and the pollutant weight vector are weightedly aggregated to generate a comprehensive pollution synergy score of the target water sample.

[0085] In actual application, by performing matrix multiplication of the standardized pollutant concentration data and the synergistic impact matrix, the overall impact of each pollutant in the current water sample due to its synergistic relationship with other pollutants is comprehensively reflected, and the pollutant synergy index vector is output as a quantitative result of the actual influence of each pollutant. It avoids the limitation of relying solely on concentration values ​​to assess the degree of pollution, fully considers the nonlinear interaction effects between pollutants, and helps to more realistically restore the synergistic amplification or mutual weakening of multiple pollutants in actual water quality impacts, providing a more scientific and explanatory data basis for subsequent evaluations. By introducing a pollutant weight vector, the synergy index vector is weighted and aggregated to output a single comprehensive pollution synergy score, which is used to express the quantitative evaluation results of the overall pollution intensity of the current water sample, facilitating horizontal water sample comparison, vertical trend analysis and management decision support.

[0086] The steps of obtaining the water body function type of the target water sample, setting the pollutant index set and threshold system for each water body function, performing water body function matching judgment on the target water sample, and outputting the function adaptability level are as follows:

[0087] Step S31, obtaining the environmental background information of the target water sample, and identifying the corresponding water body function type based on the environmental background information;

[0088] Step S32: Based on the water body function type, a corresponding pollutant index set is set for each type of water body function, and a concentration threshold value corresponding to the water body function level is set for each pollutant index;

[0089] Step S33, extracting the concentration data of various pollutants in the target water sample, and matching and determining the concentrations of various pollutants with the concentration thresholds in the pollutant index set;

[0090] Step S34: Based on the matching degree between the pollutant concentration and the concentration threshold, the matching score of the target water sample under the current water body function is calculated, and the functional adaptability level is output.

[0091] In practical applications, the specific water function type to which a water sample belongs is determined by collecting environmental background information such as its geographic location and type of use (e.g., drinking, irrigation, aquaculture, industrial). Different water functions have different pollutant focus points and standards. Clarifying the intended use of a water body in the regional environment is a prerequisite for subsequent assessment of its pollution adaptability and remediation priorities. Establishing personalized pollutant detection indicators and safe concentration limits for specific water functions forms a standard system for water function evaluation. This ensures that the evaluation standards meet the actual water quality requirements of different functional types, avoids one-size-fits-all misjudgments, and ensures the relevance and accuracy of functional evaluations. By comparing actual water sample test data against pre-defined standard thresholds, it is determined whether the water sample meets the safety requirements for each target water function for each pollutant. This provides a preliminary assessment of the sample's functional adaptability, which serves as the basis for subsequent quantitative scoring and functional grading. The matching of each pollutant item is normalized and weighted, resulting in an overall adaptability score and grading, such as excellent, good, fair, or poor. The result indicators that can ultimately be used for management and decision-making support are formed, so that the functional adaptability of water bodies has quantifiable, comparable and traceable standards, supporting the formulation of functional protection and pollution control plans.

[0092] Collect the pollutant concentration change series of the water body to be evaluated over the historical period, perform time series analysis on the concentration of each pollutant, and obtain the steps for predicting pollution trends. Specifically,

[0093] Step S41, obtaining pollutant concentration monitoring data of the water body to be evaluated in different historical periods, and constructing a pollutant concentration time series vector;

[0094] Step S42, performing missing value repair and data smoothing processing on the pollutant concentration time series vector to form time series characteristic data of pollutant concentration;

[0095] Step S43, constructing a pollution trend analysis model based on the time series characteristic data using a time series analysis method;

[0096] Step S44 , based on the pollution trend analysis model and the concentration data of multiple pollutants in the target water sample, the concentration change trend of each pollutant in the future time period is predicted to obtain a predicted pollution trend.

[0097] In practical applications, by obtaining pollutant concentration monitoring data of the water body to be evaluated at different time periods and constructing a time series vector of pollutant concentrations, the historical change trajectory of the pollution factors can be restored; then, the time series is repaired for missing values ​​and data smoothing is performed to help eliminate the interference of monitoring errors and data mutations on trend judgment, thereby improving the accuracy and stability of the analysis; then, a pollution trend analysis model is constructed using time series analysis methods to extract the periodicity, trend, or mutation characteristics of pollutant changes; finally, combined with the pollutant concentration data in the current water sample, the trend model is input for prediction, thereby obtaining the concentration change trend of each pollutant in the future period. This process can not only systematically model and dynamically analyze the pollutant evolution process of the target water body, realize the early identification of future pollution risks, but also provide a time window for water body management. Control reference, realize the active prediction and dynamic management of water environment quality.

[0098] Based on the predicted pollution trend, the steps of dynamically adjusting the comprehensive pollution synergy score and the functional adaptability level to obtain a dynamic standard assessment result of the target water sample are specifically as follows:

[0099] Step S51, dynamically adjusting the synergy index in the pollutant synergy impact matrix based on the predicted pollution trend;

[0100] Step S52: If the predicted concentration of a pollutant increases, the synergy index of the pollutant in the pollutant synergy impact matrix is ​​correspondingly amplified;

[0101] Step S53: if the predicted concentration of a pollutant decreases, the synergy index of the pollutant in the pollutant synergy influence matrix is ​​correspondingly reduced;

[0102] Step S54 , combining the dynamically adjusted pollutant synergistic impact matrix and the standardized pollutant concentration vector of the target water sample, and recalculating the comprehensive pollution synergistic score to generate a predicted pollution synergistic score;

[0103] Step S55: dynamically adjusting the functional adaptability level based on the predicted pollution trend;

[0104] Step S56: If the predicted pollutant concentration exceeds the pollutant index concentration threshold corresponding to a certain water body function, the functional adaptability level of the target water sample under the water body function is reduced to generate a predicted functional adaptability level;

[0105] Step S57: Combining the predicted pollution collaborative score and the predicted functional adaptability level, outputting the dynamic standard evaluation result of the target water sample.

[0106] In practice, pollutants do not exhibit static synergies. Future concentration trends will directly influence the strength of their synergistic effects. Dynamically adjusting the synergy index in the pollutant synergistic impact matrix allows the interactions between pollutants to evolve over time and trends, improving the timeliness and foresight of the assessment model. This ensures that synergistic effects reflect the latest expected pollution patterns, rather than static historical states, thereby avoiding lags in assessment results. By scaling the synergy index up or down, the fluctuation in the weight of concentration trends on the overall pollution synergistic impact is reflected, highlighting the dynamic contribution of pollutants to the system's potential risk. For example, pollutants with increasing concentrations are predicted to have a greater impact on water quality deterioration and should be assigned a higher synergistic impact weight. Recalculating the pollution synergy score reflects the dynamic changes in potential risk levels, providing a predictive supplement to the original static score. This improves the time sensitivity and strategic foresight of the assessment and enables a reassessment of pollution synergy risks under future pollution scenarios. Because future pollution deterioration may render currently adapted functions unsafe or unsuitable, dynamic intervention and adjustment of the functional adaptability level is necessary. Incorporating pollution trend information into the water body function assessment system avoids judging functional adaptability based solely on current conditions and helps identify potential risk points of non-adaptability to water body functions. By comparing water quality with functional thresholds, it can identify in advance when water quality will no longer meet certain uses (such as drinking, irrigation, and recreation), allowing for appropriate adjustments to the functional adaptability level and proactive early warning of water function management. By integrating the two dimensions of pollution synergy intensity and functional adaptability, it provides a dynamic assessment of future conditions, enhancing responsiveness to changing pollution risks and foresight in functional matching judgments, significantly improving the intelligent and scientific nature of water management and risk warnings.

[0107] A system for detecting and evaluating water quality in environmental engineering, which applies the above-mentioned method for detecting and evaluating water quality in environmental engineering, comprises:

[0108] The pollution detection module collects target water samples for environmental engineering, performs pollutant detection on the pre-treated target water samples, and obtains the concentration data of various pollutants in the target water samples;

[0109] The collaborative analysis module constructs a pollutant synergistic impact matrix based on multiple pollutant concentration data, calculates the synergistic index of each pollutant's impact on overall water quality, and generates a comprehensive pollution synergy score;

[0110] Functional assessment module: obtains the water function type of the target water sample, sets a pollutant index set and threshold system for each type of water function, makes a water function matching judgment for the target water sample, and outputs the functional adaptability level;

[0111] The trend prediction module collects the pollutant concentration change sequence of the water body to be evaluated over the historical period, performs time series analysis on the concentration of each pollutant, and obtains the predicted pollution trend;

[0112] The dynamic adjustment module dynamically adjusts the comprehensive pollution synergy score and the functional adaptability level based on the predicted pollution trend to obtain a dynamic standard evaluation result of the target water sample.

[0113] In practical application, the pollution detection module enables accurate detection of multiple pollutants in target water samples, providing basic data support for subsequent analysis. The collaborative analysis module reveals the synergistic relationships between various pollutants and quantifies their impact on overall water quality. The functional assessment module determines whether a water sample meets the water quality standards for its intended use and assesses its functional adaptability. The trend prediction module then analyzes historical pollutant data, predicts future water quality trends, and provides forward-looking early warnings. The dynamic adjustment module then dynamically optimizes pollution assessment results based on the predicted results, improving their timeliness and accuracy.

[0114] The above are all preferred embodiments of the present application, and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the structure, shape, and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A method for detecting and evaluating water quality in environmental engineering, characterized in that: The following steps are involved: Collect target water samples for environmental engineering, conduct pollutant detection on the pre-treated target water samples, and obtain concentration data of various pollutants in the target water samples; Based on the concentration data of multiple pollutants, a pollutant synergistic impact matrix is ​​constructed to calculate the synergistic index of each pollutant's impact on the overall water quality and generate a comprehensive pollution synergy score; Obtain the water body function type of the target water sample, set a pollutant index set and threshold system for each type of water body function, perform water body function matching judgment on the target water sample, and output the functional adaptability level; Collect the pollutant concentration change series of the water body to be evaluated over the historical period, conduct time series analysis on the concentration of each pollutant, and obtain the predicted pollution trend; Based on the predicted pollution trend, the comprehensive pollution synergy score and the functional adaptability level are dynamically adjusted to obtain a dynamic standard evaluation result of the target water sample.

2. A method for water quality detection and evaluation in environmental engineering according to claim 1, characterized in that: The steps of collecting target water samples for environmental engineering, performing pollutant detection on the pre-treated target water samples, and obtaining concentration data of multiple pollutants in the target water samples are specifically as follows: Collecting target water samples for environmental engineering and pre-treating the target water samples; According to the characteristics and properties of water pollution in environmental projects, set the pollutant items that need to be tested and select the corresponding testing methods for each pollutant; According to the detection method, the concentration of various pollutants in the pretreated target water sample is detected to obtain concentration data of multiple pollutants in the target water sample.

3. A method for detecting and evaluating water quality in environmental engineering according to claim 1, characterized in that: The steps of constructing a pollutant synergistic impact matrix based on multiple pollutant concentration data, calculating the synergistic index of each pollutant's impact on overall water quality, and generating a comprehensive pollution synergy score are specifically as follows: Based on the concentration data of various pollutants, the concentrations of various pollutants are normalized to obtain the standardized pollutant concentration vector; Based on the interaction mechanism between pollutants, a pollutant synergistic impact matrix is ​​constructed, wherein the synergistic impact matrix is ​​used to represent the synergistic relationship between any two pollutants in affecting water quality; Based on the standardized pollutant concentration vector and the pollutant synergistic impact matrix, the synergistic index of each pollutant's impact on the overall water quality is calculated to generate a comprehensive pollution synergy score.

4. A method for detecting and evaluating water quality in environmental engineering according to claim 3, characterized in that: The steps of constructing a pollutant synergistic impact matrix based on the interaction mechanism between pollutants are specifically as follows: Extracting pollutant types from the target water sample and constructing a pollutant type set; Based on historical water sample data, the interaction information between each pair of pollutants is counted to establish a pollutant interaction factor library; Based on the pollutant interaction factor library, obtaining the synergistic effect type and synergistic effect intensity between each pair of pollutants; According to the synergistic effect type and synergistic effect intensity, synergistic impact factors are set for any two pollutants in the pollutant type set to generate a pollutant synergistic impact matrix.

5. A method for detecting and evaluating water quality in environmental engineering according to claim 3, characterized in that: The step of calculating the synergy index of the impact of each pollutant on the overall water quality based on the standardized pollutant concentration vector and the pollutant synergy impact matrix to generate a comprehensive pollution synergy score is specifically as follows: Based on the standardized pollutant concentration vector and the pollutant synergistic influence matrix, performing a matrix operation on the standardized pollutant concentration vector and the pollutant synergistic influence matrix to obtain a pollutant synergistic index vector; Based on the pollutant synergy index vector, a pollutant weight vector is obtained, and the pollutant synergy index vector and the pollutant weight vector are weighted and aggregated to generate a comprehensive pollution synergy score of the target water sample.

6. A method for detecting and evaluating water quality in environmental engineering according to claim 1, characterized in that: The steps of obtaining the water body function type of the target water sample, setting a pollutant index set and a threshold system for each type of water body function, performing water body function matching determination on the target water sample, and outputting the function adaptability level are specifically as follows: Obtaining environmental background information of the target water sample, and identifying the corresponding water body function type based on the environmental background information; Based on the water body function type, a corresponding pollutant index set is set for each type of water body function, and a concentration threshold value corresponding to the water body function level is set for each pollutant index; Extracting the concentration data of various pollutants in the target water sample, and matching the concentrations of various pollutants with the concentration thresholds in the pollutant index set; Based on the degree of matching between the pollutant concentration and the concentration threshold, the matching score of the target water sample under the current water body function is calculated, and the functional adaptability level is output.

7. A method for detecting and evaluating water quality in environmental engineering according to claim 1, characterized in that: The steps of collecting the pollutant concentration change sequence of the water body to be evaluated during the historical period, performing time series analysis on the concentration of each pollutant, and obtaining the predicted pollution trend are specifically as follows: Obtain pollutant concentration monitoring data of the water body to be assessed at different historical periods and construct a pollutant concentration time series vector; Performing missing value repair and data smoothing processing on the pollutant concentration time series vector to form time series characteristic data of pollutant concentration; Based on the time series characteristic data, a pollution trend analysis model is constructed using a time series analysis method; Based on the pollution trend analysis model and the concentration data of multiple pollutants in the target water sample, the concentration change trend of each pollutant in the future time period is predicted to obtain the predicted pollution trend.

8. The method for water quality detection and evaluation in environmental engineering according to claim 1, characterized in that: The step of dynamically adjusting the comprehensive pollution synergy score and the functional adaptability level based on the predicted pollution trend to obtain a dynamic standard assessment result of the target water sample is specifically as follows: Based on the predicted pollution trend, dynamically adjusting the synergy index in the pollutant synergy impact matrix; If the predicted concentration of a pollutant increases, the synergy index of the pollutant in the pollutant synergy impact matrix is ​​amplified accordingly; If the predicted concentration of a pollutant decreases, the synergy index of the pollutant in the pollutant synergy impact matrix will be reduced accordingly; Combining the dynamically adjusted pollutant synergistic impact matrix and the standardized pollutant concentration vector of the target water sample, the comprehensive pollution synergistic score is calculated again to generate a predicted pollution synergistic score; Dynamically adjusting the functional adaptability level based on the predicted pollution trend; If the predicted pollutant concentration exceeds the pollutant index concentration threshold corresponding to a certain water body function, the functional adaptability level of the target water sample under the water body function is reduced to generate a predicted functional adaptability level; The predicted pollution collaborative score and the predicted functional adaptability level are integrated to output a dynamic standard evaluation result of the target water sample.

9. A water quality detection and evaluation system for environmental engineering, characterized in that: The method for detecting and evaluating water quality in environmental engineering according to any one of claims 1 to 8 comprises: The pollution detection module collects target water samples for environmental engineering, performs pollutant detection on the pre-treated target water samples, and obtains the concentration data of various pollutants in the target water samples; The collaborative analysis module constructs a pollutant synergistic impact matrix based on multiple pollutant concentration data, calculates the synergistic index of each pollutant's impact on overall water quality, and generates a comprehensive pollution synergy score; Functional assessment module: obtains the water function type of the target water sample, sets a pollutant index set and threshold system for each type of water function, makes a water function matching judgment for the target water sample, and outputs the functional adaptability level; The trend prediction module collects the pollutant concentration change sequence of the water body to be evaluated over the historical period, performs time series analysis on the concentration of each pollutant, and obtains the predicted pollution trend; The dynamic adjustment module dynamically adjusts the comprehensive pollution synergy score and the functional adaptability level based on the predicted pollution trend to obtain a dynamic standard evaluation result of the target water sample.

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