A Comprehensive Impact Assessment Method and System for Water Network Projects Based on Structural Equation Modeling

Abstract

This invention discloses a method and system for comprehensive impact assessment of water network projects based on structural equation modeling. The method comprises: 1) acquiring multi-source monitoring data of the water network project; 2) preprocessing the multi-source monitoring data to obtain a standard observed variable vector X; 3) calling the structural equation model assessment; the structural equation model assessment includes a measurement model and a structural model; the measurement model defines the loading relationship between observed variables and latent variables, and the structural model defines the causal path relationship between latent variables; 4) performing matrix operations based on the structural equation model assessment to calculate the comprehensive impact score S; 5) comparing the comprehensive impact score S with a preset threshold; when the comprehensive impact score S is lower than a safety threshold, generating a control command or early warning signal and sending it to the execution terminal of the water network project; then returning to step 1 to enter the next monitoring cycle. This invention directly maps the assessment score to physical control commands, realizing real-time closed-loop control based on comprehensive impact assessment.

Description

Technical Field

[0001] This invention relates to the field of water conservancy engineering technology, and more specifically, to a method and system for comprehensive impact assessment of water network engineering based on structural equation modeling. Background Technology

[0002] As a key component of national infrastructure, water network projects play a vital role in water resource allocation, flood control and drought relief, and ecological environmental protection. With the advancement of national water network construction, modern water network projects are characterized by their large scale, complex structure, and diverse influencing factors. A typical water network system not only involves hydraulic physical processes, such as water flow and pressure transmission, but also deeply integrates ecological and environmental effects with socio-economic impacts. Therefore, conducting scientific, comprehensive, and dynamic integrated impact assessments of water network projects is a crucial prerequisite for ensuring their safe operation, optimizing water resource allocation, and achieving sustainable development.

[0003] However, existing water network engineering assessment technologies still face significant technical bottlenecks in practical applications. Firstly, in terms of assessment methods, traditional methods often employ the analytic hierarchy process (AHP) or fuzzy comprehensive evaluation. These methods heavily rely on expert scoring or experience-based judgment when determining the weights of each evaluation indicator. This subjective weighting leads to differing perceptions of the importance of the same indicator among different experts, resulting in inconsistent assessment results. Secondly, once weights are determined, they are often fixed for a long period, making dynamic adjustments impossible based on changes in the actual operating conditions of the water network project, such as high-water season versus low-water season, and normal operation versus emergency dispatch. Under sudden operating conditions, static weights may lead to the underestimation of key risk indicators, resulting in misjudgments of safety, wasting data resources, and failing to objectively reflect the real-time status of the project.

[0004] Secondly, in terms of the depth of data analysis, existing assessment methods often focus on the statistical correlation between variables, making it difficult to reveal causal paths. In water network projects, observed phenomena are often the result of the combined effects of multiple potential factors, with complex nonlinear relationships between them. Therefore, traditional methods cannot distinguish between direct and indirect effects, making it difficult to answer which factor is the root cause of the decline in the overall score, resulting in a lack of targeted operation and maintenance decisions. Furthermore, the comprehensive influencing factors of water network projects include many latent variables that cannot be directly measured by sensors, such as engineering resilience and ecological health. Existing monitoring systems typically only display raw observation data, lacking the technical means to fuse multi-source observation data and map it into high-level latent variable states. This makes it difficult for managers to intuitively grasp the hidden risk status of the project, missing the best opportunity for early warning.

[0005] Secondly, regarding system architecture and real-time performance, existing assessment systems are mostly post-event assessments or periodic reports, resulting in significant delays. Assessment systems and engineering scheduling and control systems are often independent information silos, with inconsistent data standards and difficulties in interaction. Even if a risk is identified during the assessment, it cannot be automatically translated into specific control commands, such as adjusting valve openings or pump station frequencies, and sent to the actuators. This separation of assessment and control prevents the assessment system from providing real-time decision support in the event of emergencies or complex operating conditions, limiting the improvement of the intelligence level of water network projects and hindering the formation of closed-loop control. Summary of the Invention

[0006] The present invention aims to provide a comprehensive impact assessment method for water network projects based on structural equation modeling. Another objective of the present invention is to provide a comprehensive impact assessment system for water network projects based on structural equation modeling, which aims to solve the technical problems of strong subjectivity in assessment, unclear causal paths, difficulty in quantifying latent variables, and disconnect between assessment and control in the existing technology. It realizes multi-dimensional objective quantification and real-time closed-loop control of the water network project status by integrating multi-source heterogeneous monitoring data and feeding the assessment results back to the control terminal in real time.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: On the one hand, the comprehensive impact assessment method for water network engineering based on structural equation modeling described in this invention includes the following steps: Step 1: Acquire multi-source monitoring data of the water network project through data acquisition equipment. The multi-source monitoring data covers three dimensions: hydraulic operation, ecological environment and socio-economic aspects. Step 2: Use the processor to preprocess the multi-source monitoring data, including outlier removal and normalization, to obtain the standard observation variable vector X; Step 3: Invoke the structural equation evaluation model stored in memory; the structural equation evaluation model includes a measurement model and a structural model; the measurement model defines the loading relationships between observed variables and latent variables, and the structural model defines the causal path relationships between the latent variables. Step 4: Perform matrix operations based on the structural equation model to calculate the comprehensive impact score S. The specific calculation process is as follows: First, calculate the latent variable score vector ξ through the measurement model equation, and then calculate the comprehensive impact score S=W×ξ through the structural model equation, where W is the path coefficient weight vector. Step 5: Compare the comprehensive impact score S with the preset threshold. When the comprehensive impact score S is lower than the safety threshold, generate a control command or early warning signal and send it to the execution terminal of the water network project; then return to step 1 to enter the next monitoring cycle.

[0008] Furthermore, in step 1, the observation indicators of the three dimensions include: Hydraulic operation dimensions: pipeline pressure, node flow rate, water level difference; Ecological and environmental dimensions: chemical oxygen demand, ammonia nitrogen content, and vegetation cover index; Socioeconomic dimensions: water supply security rate, efficiency per unit of water consumption, and user complaint rate; The observation indicators, as exogenous observation variables of the structural model, are selected based on the physical topology of the water network project to ensure that the input of the structural equation evaluation model corresponds to the physical entity of the project.

[0009] Furthermore, the structural equation evaluation model in step 3 is obtained through offline training. The training process includes: collecting historical running data to construct an initial model; using the maximum likelihood estimation method to solve for the load matrix Λ of the measurement model and the path coefficient matrix of the structural model; checking the fit of the structural equation evaluation model through the fit index; if the fit does not meet the requirements, correcting the path connections between the latent variables until the fit index meets the preset convergence condition, and then fixing and storing the final structural equation evaluation model parameters.

[0010] Further, in step 4, the matrix operation specifically includes: multiplying the standard observation variable vector X by the inverse matrix or equivalent transformation matrix of the load matrix to obtain the latent variable score vector; and multiplying the latent variable score vector by the path coefficient weight vector to obtain the scalar form of the comprehensive influence score S.

[0011] Furthermore, in step 5, generating control commands specifically includes: if the comprehensive impact score S is lower than a preset first threshold, it is determined to be an engineering risk, and a pump station frequency reduction command or a valve closing command is generated; if the comprehensive impact score S is lower than a preset second threshold, it is determined to be an ecological risk, and an ecological water replenishment flow control command is generated; the control commands are encapsulated through an industrial communication protocol and directly drive the field actuators to act.

[0012] Furthermore, in step 2, the preprocessing of the multi-source monitoring data also includes: filling in missing data using a time series interpolation algorithm; and identifying and removing physically abnormal data using the 3σ principle.

[0013] On the other hand, the comprehensive impact assessment system for water network engineering based on structural equation modeling described in this invention includes: The data acquisition module, corresponding to step 1, is configured to physically connect to the water network project site through a sensor network, collect the multi-source monitoring data, and transmit it to the data processing module. The data processing module, corresponding to step 2, is configured to receive the multi-source monitoring data, execute cleaning and standardization algorithms, and generate the standard observation variable vector X. The model calculation module, corresponding to steps 3 and 4, is configured to read the pre-stored structural equation evaluation model parameters from the memory, perform matrix operations between the measurement model and the structural model, and output the comprehensive influence score S. The communication interface module is configured to provide communication connections with on-site equipment and execution terminals in water network engineering projects; The decision output module, corresponding to step 5, is configured to generate a control strategy based on the comprehensive impact score S and send it to the execution terminal through the communication interface module. The processor is used to coordinate the operation of the above modules and execute the computational logic; wherein, the data flow is as follows: the data acquisition module sends the raw data to the data processing module for processing, the processed vector is sent to the model calculation module, and the calculation result is sent to the decision output module.

[0014] The memory is used to store the load matrix Λ and path coefficient weight vector W of the structural equation model evaluation model, as well as the computer program. When the computer program is executed by the processor, it implements the steps of the comprehensive impact assessment method for water network engineering based on structural equation model as described in claim 1.

[0015] Furthermore, the model calculation module integrates a model verification unit, which checks the integrity of the input data before each calculation. If the data missing rate exceeds a preset ratio, a data interpolation and completion program is triggered to ensure the stability of the structural equation evaluation model solution.

[0016] Furthermore, the system also includes a human-computer interaction interface for visually displaying the scores of each latent variable and key influence paths. When the comprehensive influence score S is abnormal, the main causal path leading to the decrease in the comprehensive influence score S is highlighted.

[0017] Furthermore, the communication interface module supports Modbus TCP or IEC 104 industrial protocols, ensuring that the control commands generated by the decision output module can be recognized and executed by the existing SCADA system (data acquisition and monitoring control system) of the water network project.

[0018] The beneficial effects of this invention are as follows: By using a structural equation modeling measurement model, this invention transforms latent variables such as "engineering resilience" and "ecological health," which are difficult to measure directly, into calculable mathematical vectors. This eliminates the subjectivity of expert scoring and clarifies the direct and indirect influence relationships between hydraulic, ecological, and social factors using the path coefficients of the structural model, enabling precise identification of key causes leading to a decline in the overall score. Furthermore, this invention directly maps the assessment score to physical control commands, breaking down the data barriers between existing assessment and scheduling systems and achieving real-time closed-loop control based on comprehensive impact assessment. Simultaneously, by solidifying model parameters through offline training, online calculations are only required, resulting in high computational efficiency. This makes it suitable for industrial-grade real-time monitoring systems. Moreover, the system modules and methodological steps strictly correspond, the data flow is clear, and the industrial protocol interface ensures that the assessment results can be reliably translated into engineering actions. Attached Figure Description

[0019] Figure 1 This is a flowchart of a comprehensive impact assessment method for water network engineering based on structural equation modeling, provided by an embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram illustrating the relationship between latent variables and observed variables in the structural equation model evaluation model in this embodiment of the invention.

[0021] Figure 3 This is a block diagram of the modular architecture of a comprehensive impact assessment system for water network engineering based on structural equation model, provided by an embodiment of the present invention.

[0022] Figure 4 This is a schematic diagram of system hardware deployment and data interaction provided in an embodiment of the present invention. Detailed Implementation

[0023] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are intended to explain the present invention, but not to limit its scope of protection.

[0024] Example 1: like Figure 1 As shown in the figure, this embodiment provides a comprehensive impact assessment method for water network projects based on structural equation modeling. This method is deployed on the intelligent dispatch center server of a large-scale inter-basin water transfer project. The specific implementation steps are as follows: Step 1, Acquisition of multi-source monitoring data: Multi-source monitoring data of the water network project is acquired through data acquisition equipment; in practice, various physical sensors and business systems are deployed on-site in the water network project.

[0025] (1) Hydraulic operation dimension: The pressure of the water transmission pipeline of the water network project (unit: MPa) is collected by pressure transmitter, and the flow rate of key nodes of the water transmission trunk line (unit: m³ / s) is collected by electromagnetic flow meter, such as pumping station and water distribution node; the water level difference between the inlet and outlet pools of the pumping station (unit: m) is collected by radar water level gauge; these data are collected by remote terminal unit (RTU) with a sampling frequency of 5 minutes / time.

[0026] (2) Ecological and environmental dimension: Chemical oxygen demand (COD) (unit: mg / L) and ammonia nitrogen content (NH3-N) (unit: mg / L) of key water transfer sections (or main canals) are collected by online water quality monitoring instruments; the vegetation cover index (NDVI) (dimensionless) along the water transfer route is obtained periodically through satellite remote sensing interface.

[0027] (3) Socioeconomic dimension: The water supply guarantee rate (%) of the water receiving area is read through the water supply business system database, the unit water volume benefit (yuan / m³) is read through the financial system, and the user complaint rate (times / 10,000 households) is read through the customer service hotline system; all the above data are transmitted to the intelligent dispatch center server through the MQTT protocol to form the original dataset Draw.

[0028] Step 2, Data Preprocessing: The multi-source monitoring data is preprocessed using the processor of the intelligent dispatch center server to obtain the standard observation variable vector X.

[0029] (1) Outlier removal: Using the 3σ principle, calculate the historical mean μ and standard deviation σ of each indicator in step 1. If the current data xi satisfies |xi−μ|>3σ, it is determined to be an outlier and linear interpolation is performed using the data from the previous period.

[0030] (2) Normalization: Since the dimensions of each indicator are different (e.g., pressure is MPa, COD is mg / L), the Min-Max normalization method is used to map all data to the interval [0,1]. The calculation formula is: x_norm = (x_raw - x_min) / (x_max - x_min), where x_min and x_max are the physical limits of the historical operating range of the indicator. After processing, the standard observation variable vector X=[x1, x2, ..., x9] is obtained. ^T There are a total of 9 indicators.

[0031] Step 3, call structural equation modeling to evaluate the model: The structural equation model stored in the intelligent scheduling center server's memory is invoked; this model was trained offline using historical operating data from the past 5 years before the system went online.

[0032] (1) Definition of structural equation model evaluation: such as Figure 2 As shown, the structural equation model evaluation model includes a measurement model and a structural model; Latent variable definition: Three first-order latent variables are defined as “engineering safety status” (η1), “ecological environment health” (η2), and “social service benefits” (η3); one second-order latent variable is defined as “comprehensive impact score” S.

[0033] Measurement model: Defines the loadings between the standard observed variable X and the latent variable η, such as... Figure 2 As shown, pipeline pressure (x1), node flow rate (x2), and water level difference (x3) are mainly loaded on η1; chemical oxygen demand (COD) (x4), ammonia nitrogen content (NH3-N) (x5), and vegetation cover index (NDVI) (x6) are mainly loaded on η2; and water supply guarantee rate (x7), unit water volume benefit (x8), and user complaint rate (x9) are mainly loaded on η3.

[0034] Structural model: Defines the causal paths between latent variables; for example, η1 and η2 directly affect S, and η3 is indirectly affected by η1 and η2.

[0035] (2) Parameter loading: Read the trained load matrix Λ and path coefficient weight vector W from the memory; where Λ is a 9×3 load matrix and W is a path coefficient weight vector; these parameters are fixed values, representing the causal laws under the specific physical topology of the water network project.

[0036] Step 4, Matrix Operations and Score Calculation: Matrix operations are performed based on the structural equation evaluation model to calculate the comprehensive impact score S.

[0037] (1) Latent variable score calculation: The processor executes the measurement model equations and maps the standard observed variable vector X to the latent variable score vector ξ; the simplified calculation formula is: ξ=Λ ^(-1) X or its equivalent transformation, where ξ=[η1,η2,η3]^ T In actual calculations, the partial least squares (PLS) scoring algorithm is used to solve the problem and obtain the specific scores (between 0 and 1) of each latent variable at the current time.

[0038] (2) Calculation of comprehensive score: The processor executes the structural model equation and calculates the final comprehensive impact score S; the calculation formula is: S=W×ξ=w1η1+w2η2+w3η3, where W=[w1, w2, w3] is the path coefficient weight vector, for example W=[0.4,0.3, 0.3], which indicates that the engineering safety weight is the highest; through this step, the quantitative mapping from physical sensor data to abstract engineering status indicators is realized.

[0039] Step 5, Decision Output and Control: Compare the comprehensive impact score S with a preset threshold.

[0040] (1) Threshold Setting: The preset threshold is determined based on the statistical distribution of historical normal operation data or industry regulatory standards; in this embodiment, the first safety threshold T1 = 0.75 and the second ecological threshold T2 = 0.65 are set.

[0041] (2) Logic Judgment and Instruction Generation: If S < T1, it is determined as an engineering risk, and the system automatically generates a "pumping station frequency reduction instruction", encapsulates the instruction to reduce the frequency setting value by 5 Hz into a Modbus TCP message, and sends it to the pumping station PLC control system through the communication interface module (204); if S < T2 and the η2 score is the lowest, it is determined as an ecological risk, and the system generates an "ecological water replenishment flow setting instruction", encapsulates the instruction to increase the downstream discharge valve opening by 10% into an IEC 104 protocol message, and sends it to the gate control system; if S ≥ T1, the system generates a "normal operation" warning signal and displays a green status light on the dispatching large screen.

[0042] (3) Closed-loop Feedback: After completing this evaluation and instruction sending, the system waits for the next sampling period, returns to Step 1 to continue obtaining data, and forms a real-time monitoring closed loop.

[0043] It should be noted that the specific index selection, threshold setting, and model parameters in the above specific implementation manners are only the preferred embodiments of this case. In actual applications, those skilled in the art can adjust the types and quantities of the observation indexes or modify the path relationships of the structural equation model according to the scale and characteristics of the specific water network project. As long as their core processing logics follow the structural equation modeling and evaluation process described in this invention, they should all be included in the protection scope of this invention.

[0044] Embodiment 2 As Figure 3 and Figure 4 shown, this embodiment provides a comprehensive impact assessment system for water network projects based on a structural equation model, and this system is used to implement each step of the method described in Embodiment 1; the system includes two parts: a hardware architecture and software modules.

[0045] 1. As Figure 3 shown, the module architecture and data flow of this system are as follows: (1) Data Input Stage: The water network field sensors (external devices) transmit the original monitoring data to the data acquisition module (201) through the communication interface module (204), and the data acquisition module (201) sends the original monitoring data to the data processing module (202).

[0046] (2) Data processing stage: The data processing module (202) cleans and normalizes the raw monitoring data, generates a standard observation vector X, and sends it to the model calculation module (203).

[0047] (3) Model calculation stage: The model calculation module (203) reads the pre-stored load matrix Λ and path coefficient weight vector W from the memory (206) and performs matrix operation ξ=Λ. ^(-1) X and S=W×ξ, and the comprehensive score S is sent to the decision output module (205); in order to solve the limitations of static weights mentioned in the background technology, the memory (206) pre-stores multiple sets of model parameters corresponding to different working conditions (such as the high water season and the low water season), and the processor (207) automatically switches the matching parameter set according to the current hydrological characteristics.

[0048] (4) Decision output stage: The decision output module (205) compares the comprehensive impact score S with the preset threshold, generates control instructions or early warning signals, and sends them to the execution terminal (pump station PLC / gate controller) through the communication interface module (204).

[0049] (5) Control and Coordination: The processor (207) controls the signal ( Figure 3 (As shown by the dashed line) Coordinate the runtime sequence of each module to ensure the synchronization and real-time performance of the data flow.

[0050] 2. Hardware architecture such as Figure 4 As shown, the system is deployed on an industrial-grade server, and the hardware includes: (1) Processor (207): Used to execute data preprocessing algorithms and matrix operation logic.

[0051] (2) Memory (206): Used to store the parameter file (including load matrix Λ and path coefficient weight vector W) of the structural equation evaluation model, historical database, real-time cache and computer program, which implements the steps in Embodiment 1 when the computer program is executed by the processor.

[0052] (3) Communication interface module (204): includes Ethernet port and serial port server, supports Modbus TCP, IEC 104 and MQTT protocols, and is used to connect with sensors, RTU and PLC actuators in the water network.

[0053] 3. The software modules and their correspondence with the method steps are as follows: Figure 3 As shown, the system software includes the following modules, which work together to implement the evaluation process: (1) Data acquisition module (201) (corresponding to step 1): configured to poll the field sensors through the communication interface module (204), parse the protocol messages, convert the original physical quantities into digital signals, and timestamp them and store them in the real-time database.

[0054] (2) Data processing module (202) (corresponding to step 2): configured to read data from the real-time database, execute the 3σ anomaly detection script and the Min-Max normalization function, and output the standard observation variable vector X to the shared memory area.

[0055] (3) Model calculation module (203) (corresponding to steps 3 and 4): configured to monitor the shared memory area, and load the model parameter file in the memory (206) as soon as new data is available; the processor (207) integrates a matrix operation library (such as the BLAS library) and executes ξ=Λ^ (-1) The X and S = W × ξ operations are performed. The processor (207) also includes a model verification unit that triggers an alarm and suspends the calculation if the missing input data rate exceeds 20% to prevent incorrect evaluation.

[0056] (4) Decision output module (205) (corresponding to step 5): configured to receive the S value output by the model calculation module (203) and compare it with the preset threshold register; if the trigger condition is met, the protocol stack is called to generate a control instruction message and send it through the communication interface module (204).

[0057] (5) Human-computer interaction interface (HMI): Configured to visualize the scores of each latent variable and key impact paths; when the comprehensive impact score S is abnormal, the interface highlights the main causal path that leads to the score decline (for example, highlighting the path from "pipeline pressure" to "engineering safety") to assist human decision-making.

[0058] Technical Effect Description: This embodiment transforms the statistical tool of structural equation modeling into a concrete engineering technique through specific hardware connections and software logic. Specifically: (1) Physical binding of data and model: The observed indicators (such as pressure and COD) are directly derived from physical sensors, and the model parameters are fixed in memory (206), ensuring that the evaluation process is based on physical entities rather than pure theoretical derivation.

[0059] (2) Closed-loop control implementation: The evaluation results directly drive the PLC action, which solves the problem that the traditional evaluation system can only display and cannot control.

[0060] (3) Computational efficiency: The online phase only involves matrix multiplication, and the computation time is in the millisecond range, which meets the real-time scheduling requirements of water network projects.

[0061] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A comprehensive impact assessment method for water network engineering based on structural equation modeling, characterized in that, Includes the following steps: Step 1: Obtain multi-source monitoring data of the water network project, which covers three dimensions: hydraulic operation, ecological environment and socio-economic aspects. Step 2: Preprocess the multi-source monitoring data, including outlier removal and normalization, to obtain the standard observation variable vector X; Step 3: Invoke the structural equation model evaluation model; the structural equation model evaluation model includes a measurement model and a structural model; the measurement model defines the loading relationships between observed variables and latent variables, and the structural model defines the causal path relationships between the latent variables. Step 4: Perform matrix operations based on the structural equation model to calculate the comprehensive impact score S; Step 5: Compare the comprehensive impact score S with a preset threshold. When the comprehensive impact score S is lower than the safety threshold, generate a control command or early warning signal and send it to the execution terminal of the water network project. Then return to step 1 to enter the next monitoring cycle.

2. The comprehensive impact assessment method for water network engineering based on structural equation modeling as described in claim 1, characterized in that: In step 1, the observation indicators of the three dimensions include: Hydraulic operation dimensions: pipeline pressure, node flow rate, water level difference; Ecological and environmental dimensions: chemical oxygen demand, ammonia nitrogen content, and vegetation cover index; Socioeconomic dimensions: water supply security rate, efficiency per unit of water consumption, and user complaint rate; The observation indicators, as exogenous observation variables of the structural model, are selected based on the physical topology of the water network project.

3. The comprehensive impact assessment method for water network engineering based on structural equation modeling as described in claim 1 or 2, characterized in that: In step 3, the structural equation model evaluation model is obtained through offline training. The training process includes: collecting historical running data to build an initial model; using the maximum likelihood estimation method to solve for the load matrix Λ of the measurement model and the path coefficient matrix of the structural model; and using the fit index to test the fit of the structural equation model evaluation model. If the fit does not meet the requirements, the path connections between the latent variables are corrected until the fit index meets the preset convergence condition.

4. The method for comprehensive impact assessment of water network engineering based on structural equation modeling as described in claim 1 or 2, characterized in that: In step 4, the matrix operation specifically includes: multiplying the standard observation variable vector X by the inverse matrix or equivalent transformation matrix of the load matrix to obtain the latent variable score vector; and multiplying the latent variable score vector by the path coefficient weight vector to obtain the comprehensive influence score S.

5. The comprehensive impact assessment method for water network engineering based on structural equation modeling as described in claim 1 or 2, characterized in that: Step 5, generating control commands or warning signals includes: If the comprehensive impact score S is lower than a preset first threshold, it is determined to be an engineering risk, and a pump station frequency reduction command or a valve closing command is generated; if the comprehensive impact score S is lower than a preset second threshold, it is determined to be an ecological risk, and an ecological water replenishment flow control command is generated.

6. The comprehensive impact assessment method for water network engineering based on structural equation modeling as described in claim 1, characterized in that: Step 2, the preprocessing of the multi-source monitoring data also includes: filling in missing data using time series interpolation algorithms; and identifying and removing physically abnormal data using the 3σ principle.

7. A comprehensive impact assessment system for water network engineering based on structural equation modeling, characterized in that: include: The data acquisition module is configured to physically connect to the water network project site via a sensor network, collect the multi-source monitoring data, and transmit it to the data processing module; The data processing module is configured to receive multi-source monitoring data, execute cleaning and standardization algorithms, and generate the standard observation variable vector X. The model calculation module is configured to read the pre-stored structural equation evaluation model parameters from the memory, perform matrix operations between the measurement model and the structural model, and output the comprehensive influence score S; The communication interface module is configured to provide communication connections with on-site equipment and execution terminals in water network engineering projects; The decision output module is configured to generate a control strategy based on the comprehensive impact score S and send it to the execution terminal through the communication interface module. The processor is used to coordinate the operation of the above modules and execute computational logic; The memory is used to store the load matrix Λ and path coefficient weight vector W of the structural equation model evaluation model, as well as the computer program. When the computer program is executed by the processor, it implements the steps of the comprehensive impact assessment method for water network engineering based on structural equation model as described in claim 1.

8. The system of the comprehensive impact assessment method for water network engineering according to claim 7, characterized in that: The model calculation module integrates a model verification unit, which checks the integrity of the input data before each calculation. If the data missing rate exceeds a preset ratio, the data interpolation and completion program is triggered.

9. The system of the comprehensive impact assessment method for water network engineering according to claim 7, characterized in that: It also includes a human-computer interaction interface for visually displaying the scores and influence paths of each latent variable, and displaying the causal path when the comprehensive influence score S is abnormal.

10. The system of the comprehensive impact assessment method for water network engineering according to claim 7, characterized in that: The communication interface module supports Modbus TCP or IEC 104 industrial protocol.

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