CN117893020A

CN117893020A - Hydraulic engineering quality safety risk assessment method

Info

Publication number: CN117893020A
Application number: CN202410079422.6A
Authority: CN
Inventors: 刘冬梅
Original assignee: Chengde Wulie River Channel And Rubber Dam Management Center
Current assignee: Chengde Wulie River Channel And Rubber Dam Management Center
Priority date: 2024-01-19
Filing date: 2024-01-19
Publication date: 2024-04-16

Abstract

The invention provides a hydraulic engineering quality safety risk assessment method, and belongs to the technical field of hydraulic engineering. The hydraulic engineering quality safety risk assessment method comprises the following steps: various data in the hydraulic engineering construction process are collected, and a hydraulic engineering risk database is constructed; analyzing data in a hydraulic engineering risk database, and identifying potential risk factors and risk events and relations between the potential risk factors and the risk events; constructing a risk system framework reflecting the risk logic association; according to different risk types, levels and grades, selecting proper risk evaluation methods and standards, establishing a risk evaluation index system, determining the weight, threshold and grading parameters of risk evaluation, carrying out quantitative or descriptive evaluation on risks, and outputting risk evaluation results and reports; according to the risk evaluation result, making targeted safety control measures and emergency plans; a closed-loop risk management mechanism is established through periodic assessment, analysis and continuous improvement.

Description

Hydraulic engineering quality safety risk assessment method

Technical Field

The application relates to the technical field of hydraulic engineering, in particular to a hydraulic engineering quality safety risk assessment method.

Background

With the development of society and the acceleration of urban process, hydraulic engineering plays a vital role in infrastructure construction. However, the diversity and complexity involved in the construction of hydraulic engineering presents a series of quality safety hazards and risks. Therefore, development of a high-efficiency, comprehensive and scientific hydraulic engineering quality safety risk assessment method is particularly urgent.

Traditional hydraulic engineering quality safety assessment methods are often limited to local factors, and lack of global view results in difficulty in comprehensively grasping sources and propagation paths of risks. Meanwhile, the existing method has defects in data collection, analysis and comprehensive evaluation, and scientific and systematic evaluation of a complex hydraulic engineering system is difficult to realize. Therefore, we propose a hydraulic engineering quality security risk assessment method to overcome the limitations of the existing methods and better meet the increasing hydraulic engineering construction demands.

Disclosure of Invention

In order to overcome the drawbacks of the prior art, an object of the present invention is to provide a hydraulic engineering quality security risk assessment method, which comprises the following steps.

And step 1, collecting various data in the hydraulic engineering construction process, including data in engineering design, construction, materials, equipment, environment and personnel, preprocessing the collected data and constructing a hydraulic engineering risk database.

And 2, analyzing data in a hydraulic engineering risk database, and identifying potential risk factors and risk events and relations among the potential risk factors and the risk events.

And step 3, constructing a risk system framework reflecting the risk logic association through risk evaluation and risk event association analysis, and providing basis for subsequent risk management.

And 4, selecting proper risk evaluation methods and standards according to different risk types, levels and grades, establishing a risk evaluation index system, determining the weight, threshold and grading parameters of risk evaluation, carrying out quantitative or descriptive evaluation on the risk, and outputting a risk evaluation result and a report.

And 5, formulating targeted safety management and control measures and emergency plans according to risk evaluation results, wherein the targeted safety management and control measures and emergency plans comprise prevention, control, transfer and bearing of risks, and monitoring, reporting, treatment and recovery processes of the risks.

And 6, establishing a closed-loop risk management mechanism, continuously improving the effects and the efficiency of risk identification, evaluation and coping through periodic evaluation, analysis and continuous improvement, perfecting a risk management system, and continuously optimizing a risk management and control level.

Further, the concrete steps of constructing the hydraulic engineering risk database are as follows.

The purpose, range, function and user requirements of the hydraulic engineering risk database are determined, and the source, type, format, quality and safety requirements of the data are determined.

And designing a data structure of the hydraulic engineering risk database, namely an organization mode and a storage mode of the data according to the result of the demand analysis.

And designing a data model of the hydraulic engineering risk database according to the result of the data structure design, namely, logically representing and conceptualizing the data.

And (3) according to the result of the data model design, formulating a data element standard of the hydraulic engineering risk database, namely, the specification of the minimum unit and the basic element of the data.

And (3) establishing a data dictionary management system of the hydraulic engineering risk database according to the result established by the data element standard, namely, managing the description and the annotation of the data.

And importing the collected hydraulic engineering risk data into a hydraulic engineering risk database according to the result of the data dictionary management, and performing data cleaning, checking, conversion, updating and backup operations.

Further, step 2 includes the following steps.

And 2.1, performing basic descriptive statistical analysis on the data in the hydraulic engineering risk database, wherein the basic descriptive statistical analysis comprises calculating the average value, standard deviation, maximum value, minimum value, frequency and percentage of the data so as to know the basic distribution and characteristics of the data.

And 2.2, performing association analysis on the data in the hydraulic engineering risk database to find out the relativity and causality in the data so as to identify potential risk factors and risk events and the relationship between the potential risk factors and the risk events.

And 2.3, carrying out cluster analysis on the data in the hydraulic engineering risk database to divide the data into a plurality of similar subsets or categories, thereby identifying different risk types and risk grades.

And 2.4, carrying out classification analysis on the data in the hydraulic engineering risk database to establish a classification model or a prediction model of the data, thereby identifying influence factors and influence degrees of risks, and occurrence probability and consequences of the risks.

And 2.5, carrying out regression analysis on the data in the hydraulic engineering risk database to establish a regression model or a fitting model of the data, thereby identifying the change trend and the change rule of the risk, and the influence factors and the influence degree of the risk.

And 2.6, carrying out time sequence analysis on the data in the hydraulic engineering risk database to analyze the time sequence characteristics and the time sequence modes of the data, thereby identifying the periodicity, the seasonality, the trending and the randomness of the risk, and the development trend and the prediction result of the risk.

And 2.7, carrying out spatial analysis on the data in the hydraulic engineering risk database to analyze the spatial distribution characteristics and the spatial distribution modes of the data, thereby identifying the spatial distribution and the spatial difference of risks, and the spatial influence factors and the spatial influence ranges of the risks.

Further, step 3 includes the following steps.

And quantitatively or qualitatively evaluating the risk by adopting a proper risk evaluation method according to the occurrence probability and the influence degree of the risk, and calculating a risk value or a risk index.

And classifying the risks into different types, grades and grades according to the risk evaluation results.

And determining the co-cause relationship and the mutual induction mechanism between risk events by using a correlation analysis method, and analyzing the sources, influencing factors, propagation paths and consequences of risks to form a risk system framework and a propagation path.

And the risk system framework and the propagation path are presented in the form of diagrams or characters, so that the structure, the characteristics and the rules of the risk are clearly displayed, and basis is provided for risk management and control and response.

Further, a risk evaluation index system is established, and the weight, the threshold value and the grading parameters of risk evaluation are determined, specifically.

And selecting a proper evaluation index and a corresponding quantitative or descriptive index value according to the characteristics and the evaluation purpose of the hydraulic engineering.

And quantitatively weighting the evaluation index by using an analytic hierarchy process to reflect the importance of the index.

The threshold value of risk assessment, i.e. the criterion for classifying the risk level, is determined.

Further, the risk is quantitatively or descriptively evaluated, and a risk evaluation result and a report are output, specifically.

And calculating or analyzing the risk according to the selected evaluation method to obtain the numerical value or grade of the risk.

And (3) comprehensively evaluating risks of single index or multiple indexes by combining the analysis theory to obtain the overall risk level of the engineering.

And (3) creating a risk evaluation report comprising an engineering introduction, an evaluation basis, an evaluation method and standard, an evaluation index system, an evaluation result and conclusion, safety control measures and an emergency plan.

Further, step 5 includes the following steps.

And according to the risk evaluation result, determining the possibility and the result of the risk, analyzing the influence range and the hazard degree of the risk, and determining the management priority and the emergency response level of the risk.

And selecting proper risk management and control measures and emergency plan types, and corresponding evaluation models, tools and indexes according to the characteristics and evaluation purposes of the risk.

And establishing a risk management and control measure and emergency plan index system, wherein the risk management and control measure and emergency plan index system comprises a risk identification index, a risk analysis index, a risk evaluation index, a risk control index, a risk emergency index, and a relation and logic between indexes.

And determining the weight, the threshold value and the grading parameters of the risk management and control measures and the emergency plan, namely, giving corresponding weight to each index, sorting and prioritizing according to the importance and urgency of the risk, and setting acceptable range of the risk and grading standard of the risk grade.

And (3) managing and controlling risks and compiling an emergency plan, namely, formulating corresponding managing and controlling measures and emergency treatment programs for each risk according to the selected managing and controlling measures and plan types to obtain the managing and controlling modes and the emergency plan of the risks.

And outputting results and reports of the risk management and control measures and the emergency plans, namely, presenting the management and control and emergency processes and results in the form of characters, charts and matrixes, wherein the results and reports comprise types, levels, management and control measures, the emergency plans and risk management advice contents of risks, and description of limitation and uncertainty of management and emergency.

Further, step 6 includes the following steps.

Step 6.1, establishing a risk management performance evaluation index system: according to the targets, content, processes and results of risk management, indexes of risk management performance assessment are determined, including risk identification rate, risk control rate, risk disposal rate, risk loss rate, risk management cost-benefit ratio, and corresponding weights, standards and methods.

Step 6.2, periodically developing risk management performance assessment: and according to the risk management performance evaluation index system, periodically collecting, sorting and analyzing related data and information of risk management, calculating scores of various indexes, comprehensively evaluating the effect and efficiency of risk management, and outputting a risk management performance evaluation report.

Step 6.3, analyzing the advantages and disadvantages of risk management: analyzing the advantages and the disadvantages of the risk management according to the risk management performance evaluation report, finding out the problems and reasons of the risk management, and determining the improvement direction and the aim of the risk management.

Step 6.4, improvement measures and suggestions are provided: according to the improvement direction and the aim of the risk management, measures and suggestions for improving the risk management are provided, wherein the measures and suggestions comprise perfecting a risk management system, optimizing a risk management flow, improving the risk management capability and enhancing the risk management culture, and a risk management improvement scheme is formed.

Step 6.5, perfecting a risk management system and a process: according to the risk management improvement scheme, a risk management system and a risk management flow are continuously perfected, the risk management level is improved, and continuous improvement of risk management is realized.

Further, in step 6.1, a hierarchical analysis method is adopted to build a risk management performance evaluation index system, and the specific steps are as follows.

The risk management performance assessment problem is divided into a target layer, a criterion layer and a scheme layer, wherein the target layer is risk management performance assessment, the criterion layer is an index of risk management performance assessment, and the scheme layer is an object of risk management performance assessment.

For each layer, the relative importance between the factors is given using expert scoring: a scale of 1-9 is adopted, wherein 1 represents that two factors are equally important, 9 represents that one factor is extremely important than the other factor, and the middle number represents importance of different degrees; a judgment matrix a= (a _ij)_m×m) is constructed according to the scoring, wherein a _ij represents importance of the ith factor relative to the jth factor, and m represents the number of factors.

For each judgment matrix, a weight vector W, w= (W ₁,w₂,…,w_m)^T, where W _i represents the weight of the ith factor, satisfying W _i≥0,w₁+w₂…+w_i…+w_m =1) of each factor is solved by using a eigenvalue method.

For each judgment matrix, the consistency ratio CR is calculated by utilizing the consistency index CI and the average random consistency index RI, the consistency of the judgment matrix is checked, and the CR is less than 0.1, otherwise, the judgment matrix is required to be modified, and the specific formula is as follows: CI= (lambda _max -n)/(n-1), where lambda _max is the maximum eigenvalue of the decision matrix and n is the order of the decision matrix; RI is a constant corresponding to the difference in n, wherein: when n=1, ri=0; when n=2, ri=0; when n=3, ri=0.58; when n=4, ri=0.9; when n=5, ri=1.12; when n=6, ri=1.24; when n=7, ri=1.32; when n=8, ri=1.41; when n=9, ri=1.45; when n=10, ri=1.49; cr=ci/RI, if CR < 0.1, then the consistency of the decision matrix is accepted, otherwise the decision matrix needs to be modified.

And combining the weight vectors of all the layers by using a hierarchical total sequencing method to obtain the comprehensive weights of all the factors of the scheme layer, and sequencing the factors of the scheme layer according to the magnitude of the comprehensive weights to obtain the risk management performance evaluation result.

Further, in step 6.2, a balanced score card algorithm is adopted to evaluate risk management performance, and the specific steps are as follows.

Targets for risk management performance assessment are determined, including reducing risk loss, improving risk control capability, optimizing risk management processes, and improving risk management levels.

And determining indexes of risk management performance evaluation, and selecting proper indexes according to four dimensions.

And (5) giving the weight of each dimension and each index by adopting an expert scoring method.

And a five-level evaluation method is adopted to give the standards of the quality, the good quality, the medium quality, the poor quality and the inferior quality of each index.

The scores of the quality, the good, the middle, the bad and the inferior of each index are given by adopting a percentage system.

And calculating the total score of the risk management performance evaluation, namely the comprehensive evaluation value of the risk management, and calculating the total score of the risk management performance evaluation according to the weights and the scores of the dimensions and the indexes.

Compared with the prior art, the application has at least the following technical effects or advantages.

The application can effectively collect, analyze, evaluate, manage and improve various risks in the hydraulic engineering construction process, improve the quality and safety level of the hydraulic engineering, prevent and reduce the occurrence of hydraulic engineering accidents, ensure the smooth completion and operation of the hydraulic engineering and provide a guarantee for the sustainable development of the hydraulic engineering.

Drawings

Fig. 1 is a schematic flow chart of a hydraulic engineering quality security risk assessment method disclosed by the embodiment of the application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention become more apparent, the technical solutions in the embodiments of the present invention will be described in more detail below with reference to the accompanying drawings in the embodiments of the present invention. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some, but not all, embodiments of the invention.

All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The embodiments described below, together with the words of orientation, are exemplary and intended to explain the invention and should not be taken as limiting the invention.

As shown in FIG. 1, the hydraulic engineering quality safety risk assessment method comprises the following steps.

And step 1, collecting various data in the hydraulic engineering construction process, including data in engineering design, construction, materials, equipment, environment and personnel, preprocessing the collected data and constructing a hydraulic engineering risk database. As a first step in the assessment of the quality and safety risk of hydraulic engineering, step 1 requires the comprehensive collection of data concerning the various stages of engineering construction, including engineering design, construction, materials, equipment, environment and personnel related data. Sources of data include design documentation, construction records, material inspection reports, equipment operation data, environmental monitoring data, personnel training and qualification information, and the like. The data preprocessing process comprises data cleaning, missing value processing, abnormal value detection and data standardization, so that the quality and the integrity of data are ensured, and a reliable basis is provided for subsequent analysis and evaluation. Finally, a hydraulic engineering risk database is constructed so that the data can be systematically managed and utilized.

And 2, analyzing data in a hydraulic engineering risk database, and identifying potential risk factors and risk events and relations among the potential risk factors and the risk events. Potential risk factors and risk events are identified by deep analysis of data in a hydraulic engineering risk database, using various statistical and data mining techniques, including understanding the basic distribution and characteristics of the data using descriptive statistical methods, performing associative analysis to discover correlations and causal relationships in the data, and classifying the data into different subsets or categories by cluster analysis. The goal of this step is to fully understand the potential risks present in hydraulic engineering from multiple dimensions, ensure that all possible risk factors are considered, and to conduct a detailed analysis in the risk assessment.

And step 3, constructing a risk system framework reflecting the risk logic association through risk evaluation and risk event association analysis, and providing basis for subsequent risk management. The risk system framework of risk logic association can clearly show the relation among different risk factors to form a risk logic structure. The risk system framework provides basis for subsequent risk management, and helps decision makers to better understand key influencing factors and propagation paths of risks, so that corresponding risk management measures can be taken in a targeted manner.

And 4, selecting proper risk evaluation methods and standards according to different risk types, levels and grades, establishing a risk evaluation index system, determining the weight, threshold and grading parameters of risk evaluation, carrying out quantitative or descriptive evaluation on the risk, and outputting a risk evaluation result and a report. The goal of this step is to quantitatively or descriptively evaluate risk, outputting specific evaluation results and reports. The evaluation method can reflect the severity of risks and provide effective basis for subsequent safety control and emergency plans.

And 5, formulating targeted safety management and control measures and emergency plans according to risk evaluation results, wherein the targeted safety management and control measures and emergency plans comprise prevention, control, transfer and bearing of risks, and monitoring, reporting, treatment and recovery processes of the risks. The goal of this step is to build a powerful set of management systems that not only provide a planned management and management of risks, but also allow rapid response to the needs of different risk events.

And 6, establishing a closed-loop risk management mechanism, continuously improving the effects and the efficiency of risk identification, evaluation and coping through periodic evaluation, analysis and continuous improvement, perfecting a risk management system, and continuously optimizing a risk management and control level. The closed-loop mechanism is beneficial to the continuous optimization and perfection of a risk management system, and ensures that the risk management system can adapt to the continuously-changing engineering and environmental conditions. Meanwhile, the quality and the safety level of the hydraulic engineering can be continuously improved by establishing a continuous improvement mechanism of risk management.

The purpose, range, function and user requirements of the hydraulic engineering risk database are determined, and the source, type, format, quality and safety requirements of the data are determined. The purpose of the hydraulic engineering risk database is clearly defined, and whether the hydraulic engineering risk database is used for risk assessment, management, monitoring or other purposes is determined. The scope of the database is defined, including the detailed requirements of the covered hydraulic engineering type, stage and related data. The main functions of the database, such as data storage, analysis, report generation, etc., are specified. Finally, primary users of the database are identified to ensure that their needs are met.

And designing a data structure of the hydraulic engineering risk database, namely an organization mode and a storage mode of the data according to the result of the demand analysis. And determining the organization mode and the storage mode of the data, including the design of a table, the establishment of a relation and the connection between the data. The database can be ensured to effectively store and retrieve various risk related data, and simultaneously the expandability and the performance of the database are considered.

And designing a data model of the hydraulic engineering risk database according to the result of the data structure design, namely, logically representing and conceptualizing the data. And using a proper data model, such as an entity-relation model, to clearly describe various aspects of hydraulic engineering, and establishing relation and dependence between different data. This helps to ensure the flexibility and understandability of the database.

And (3) according to the result of the data model design, formulating a data element standard of the hydraulic engineering risk database, namely, the specification of the minimum unit and the basic element of the data. Various data types, formats, units, and possible ranges of values are explicitly defined. Consistency and normalization of the data element criteria is ensured so that different users can understand and use the information in the database.

And (3) establishing a data dictionary management system of the hydraulic engineering risk database according to the result established by the data element standard, namely, managing the description and the annotation of the data. The data dictionary is used for recording definitions, attributes, relationships and specifications of various data elements in the database. This helps to maintain consistency of the database, improves the understandability of the data, and helps the user to better understand the information in the database.

And importing the collected hydraulic engineering risk data into a hydraulic engineering risk database according to the result of data dictionary management, and performing data cleaning, checking, conversion, updating and backup operations to ensure the quality and the integrity of the data. This includes handling duplicates, deletions, errors, or outliers and ensuring that the data conforms to previously designed data standards and structures.

Further, step 2 includes the following steps.

In step 2.1, the data in the hydraulic engineering risk database is subjected to descriptive statistical analysis, and the following steps can be adopted: according to research purposes and problems, selecting one or more variables in a hydraulic engineering risk database, such as risk types, risk grades, risk influences, risk control measures and the like; selecting proper software, and selecting proper software for descriptive statistical analysis, such as Excel, SPSS, R, python, and the like according to the data type and analysis requirements; importing data in a hydraulic engineering risk database into selected software, checking the integrity and accuracy of the data, and processing missing values, abnormal values and the like; calculating descriptive statistical indexes of the selected variables, such as average value, standard deviation, maximum value, minimum value, frequency, percentage and the like, by using built-in functions or custom functions of software; outputting descriptive statistics results, and outputting the results of the descriptive statistics indexes into tables or graphs, such as frequency tables, histograms, bin graphs, pie charts and the like by utilizing the output function of software; interpreting descriptive statistics, interpreting the meaning of descriptive statistics of selected variables, such as distribution, concentration, dispersion, skewness, kurtosis, etc., according to the output table or graph.

In step 2.2, the correlation analysis can be performed on the data in the hydraulic engineering risk database, and a correlation analysis method can be adopted, which comprises the following specific steps: according to the type and distribution of the data, a proper correlation analysis method is selected, such as the pearson correlation coefficient is suitable for continuous variable and normally distributed data, the spearman correlation coefficient is suitable for sequential variable and non-normally distributed data, and the Kelendel correlation coefficient is suitable for nominal variable and non-parameter data; calculating the results of correlation analysis among variables, such as correlation coefficients, significance levels, confidence intervals and the like, wherein the range of the values of the correlation coefficients is between-1 and 1, the larger the absolute value is, the stronger the correlation is, positive values are positive correlations, negative values are negative correlations, and 0 is no correlation; based on the results of the correlation analysis, the meaning of the correlation between the variables, such as the magnitude and direction of the correlation coefficient, the significance level, the range of confidence intervals, etc., is interpreted, taking care to distinguish between the correlation and causality without over-interpreting the results of the correlation.

In step 2.3, the data in the hydraulic engineering risk database is subjected to cluster analysis, and the following steps can be adopted: selecting variables to be analyzed, and selecting one or more variables in a hydraulic engineering risk database, such as risk events, risk influences, risk probabilities, risk control measures and the like, according to research purposes and problems; selecting proper software, and selecting proper software for cluster analysis according to the data type and analysis requirements, such as Excel, SPSS, R, python; importing data in a hydraulic engineering risk database into selected software, checking the integrity and accuracy of the data, and processing missing values, abnormal values and the like; the data is normalized or standardized, the influence of the dimension and the scale of the data is eliminated, and the clustering effect is improved; selecting a proper clustering method, such as K-means clustering, hierarchical clustering, density clustering, fuzzy clustering and the like, according to the characteristics and purposes of the data; determining parameters of the clusters, such as the number of the clusters, the centers of the clusters, the distance measurement of the clusters, the stopping criteria of the clusters and the like, according to the requirements of a clustering method; calculating clustering results of the data, such as labels of the clusters, centers of the clusters, distances of the clusters, quality of the clusters and the like by using a formula or software; outputting the clustering result into a table or graph by using the output function of software, such as a clustering matrix, a clustering tree diagram, a clustering scatter diagram, a clustering radar diagram and the like; according to the output table or graph, the meaning of the clustering result of the data, such as the characteristics of the clusters, the differences of the clusters, the meaning of the clusters and the like, is interpreted.

In step 2.4, the data in the hydraulic engineering risk database is classified and analyzed, and the following steps can be adopted: according to research purposes and problems, selecting one or more variables in a hydraulic engineering risk database, such as risk events, risk influences, risk probabilities, risk control measures and the like; selecting proper software for classification analysis, such as Excel, SPSS, R, python, and the like, according to the data type and analysis requirements; importing data in a hydraulic engineering risk database into selected software, checking the integrity and accuracy of the data, and processing missing values, abnormal values and the like; the data is normalized or standardized, the influence of the dimension and the scale of the data is eliminated, and the classification effect is improved; selecting a proper classification method, such as decision trees, support vector machines, naive Bayes, neural networks, random forests and the like, according to the characteristics and purposes of the data; determining classified parameters such as a splitting criterion, a kernel function, a priori probability, an activation function, the number of trees and the like according to the requirements of a classification method; calculating classification results of data, such as classification labels, classification accuracy, classification confusion matrixes, classification important variables and the like, by using formulas or software; outputting the classification result into a table or a graph by using the output function of software, such as a classified tree diagram, a classified boundary diagram, a classified important variable diagram and the like; according to the output table or graph, the meaning of the classification result of the data, such as the rule of classification, the performance of classification, the influence factor of classification, etc., is interpreted.

In step 2.5, regression analysis is performed on the data in the hydraulic engineering risk database, and the following steps may be adopted: according to research purposes and problems, selecting one or more variables in a hydraulic engineering risk database, such as risk events, risk influences, risk probabilities, risk control measures and the like; selecting proper software for regression analysis, such as Excel, SPSS, R, python, etc., according to the data type and analysis requirement; importing data in a hydraulic engineering risk database into selected software, checking the integrity and accuracy of the data, and processing missing values, abnormal values and the like; normalizing or standardizing the data, eliminating the influence of the dimension and scale of the data, and improving the regression effect; selecting proper regression methods, such as linear regression, multiple regression, nonlinear regression, logistic regression and the like, according to the characteristics and purposes of the data; determining regression parameters such as regression coefficients, intercept, error terms and the like according to the requirements of a regression method; calculating regression results of the data, such as regression equations, regression coefficients, regression saliency, regression fitting degree and the like by using formulas or software; outputting the regression result to a table or graph, such as a regression scatter diagram, a regression linear diagram, a regression residual diagram and the like, by using the output function of software; according to the output table or graph, the meaning of the regression result of the data, such as the interpretation of the regression equation, the meaning of the regression coefficient, the level of regression significance, the magnitude of regression fitting degree and the like, is interpreted.

In step 2.6, the time sequence analysis is performed on the data in the hydraulic engineering risk database, and the following steps can be adopted: according to research purposes and problems, selecting one or more variables in a hydraulic engineering risk database, such as risk events, risk influences, risk probabilities, risk control measures and the like; according to the data type and analysis requirements, selecting proper software for time sequence analysis, such as Excel, SPSS, R, python; importing data in a hydraulic engineering risk database into selected software, checking the integrity and accuracy of the data, and processing missing values, abnormal values and the like; carrying out stationarity test and differential processing on the data, eliminating the non-stationarity and seasonality of the data, and improving the effect of time sequence analysis; selecting proper time sequence analysis methods such as autocorrelation function, partial autocorrelation function, white noise test, stationarity test, unit root test, ARIMA model, ARCH model, GARCH model and the like according to the characteristics and purposes of data; determining parameters of time sequence analysis, such as hysteresis order, autoregressive coefficient, moving average coefficient, differential order, conditional variance and the like, according to the requirement of the time sequence analysis method; calculating a time sequence analysis result of the data, such as an autocorrelation coefficient, a partial autocorrelation coefficient, a p value of a white noise test, a p value of a stationarity test, a p value of a unit root test, an equation of an ARIMA model, an equation of an ARCH model, an equation of a GARCH model and the like by using a formula or software; outputting the time sequence analysis result to a table or a graph, such as an autocorrelation graph, a partial autocorrelation graph, a residual graph, a prediction graph and the like by utilizing the output function of software; the meaning of the time sequence analysis result of the data is interpreted according to the output table or graph, such as stationarity, periodicity, trend, randomness, predictability and the like.

In step 2.7, the data in the hydraulic engineering risk database is spatially analyzed, and the following steps may be adopted: according to research purposes and problems, selecting one or more variables in a hydraulic engineering risk database, such as risk events, risk influences, risk probabilities, risk control measures and the like; according to the data type and analysis requirement, selecting proper software to perform space analysis, such as ArcGIS, QGIS, mapInfo; importing data in a hydraulic engineering risk database into selected software, checking the integrity and accuracy of the data, and processing missing values, abnormal values and the like; performing projection conversion, space matching, space interpolation and other treatments on the data, eliminating the space error and space discontinuity of the data, and improving the effect of space analysis; according to the characteristics and purposes of the data, selecting a proper space analysis method, such as space statistics, space clustering, space regression, space interpolation, space simulation and the like; determining parameters of spatial analysis, such as spatial weight, clustering number, regression model, interpolation method, simulation rule and the like, according to the requirements of the spatial analysis method; calculating a spatial analysis result of the data, such as a spatial distribution diagram, a spatial cluster diagram, a spatial regression diagram, a spatial interpolation diagram, a spatial simulation diagram and the like by using a formula or software; outputting the spatial analysis result to a table or a graph by using the output function of software, such as a spatial distribution matrix, a spatial clustering matrix, a spatial regression equation, a spatial interpolation function, a spatial simulation model and the like; according to the output table or graph, the meaning of the spatial analysis result of the data, such as the characteristics of spatial distribution, the category of spatial clustering, the relation of spatial regression, the precision of spatial interpolation, the reliability of spatial simulation and the like, is explained.

Further, step 3 includes the following steps.

And 3.1, quantitatively or qualitatively evaluating the risk by adopting a proper risk evaluation method according to the occurrence probability and the influence degree of the risk, and calculating a risk value or a risk index.

And 3.2, classifying risks into different types, grades and grades according to the risk evaluation result.

And 3.3, determining a co-cause relation and a mutual induction mechanism between risk events by using a correlation analysis method, and analyzing sources, influencing factors, propagation paths and consequences of risks to form a risk system framework and a propagation path.

And 3.4, presenting the risk system framework and the propagation path in a chart or text form, clearly displaying the structure, the characteristics and the rules of the risk, and providing basis for risk management and control and response.

In step 3.1, quantitative evaluation is performed by using a risk rate method, wherein the risk rate method is to define a risk as a product of probability of risk occurrence and risk loss, i.e., r=p×c, where R is a risk value, P is probability of risk occurrence, and C is risk loss; the qualitative evaluation is carried out by adopting a fuzzy comprehensive evaluation method, wherein the fuzzy comprehensive evaluation method is a method for comprehensively evaluating risks by utilizing a fuzzy mathematic principle and expressing the occurrence probability and the influence degree of the risks by using a fuzzy language or a fuzzy set and then utilizing a fuzzy matrix or a fuzzy relation to obtain fuzzy grades or fuzzy values of the risks.

In step 3.3, the correlation analysis method is used to determine the co-cause relationship and the mutual induction mechanism between risk events, and the following steps may be adopted: selecting one or more risk events in a risk database, such as reservoir dam break, debris flow, flood, etc., according to research purposes and problems; according to the data type and analysis requirements, selecting proper software for relevant analysis, such as Excel, SPSS, R, python and the like; importing data such as occurrence probability, influence degree and the like of risk events in a risk database into selected software, checking the integrity and accuracy of the data, and processing missing values, abnormal values and the like; carrying out normal inspection, variable conversion and other treatments on the data, enabling the data to accord with the assumption conditions of the correlation analysis, and improving the effect of the correlation analysis; selecting a proper correlation analysis method, such as a Pearson correlation coefficient or a Spearman correlation coefficient, according to the characteristics and purposes of the data; determining parameters of correlation analysis, such as significance level, confidence interval, hypothesis testing and the like according to requirements of a correlation analysis method; calculating correlation coefficients between risk events, such as Pearson correlation coefficients or Spearman correlation coefficients, by using a formula or software; outputting the correlation analysis result to a table or a graph, such as a correlation matrix, a correlation graph, a scatter graph and the like, by using an output function of software; according to the output table or graph, explaining the meaning of the correlation analysis result between the risk events, such as correlation direction, correlation degree, correlation significance and the like; and determining the co-cause relation and the mutual induction mechanism between risk events according to the related analysis results, analyzing sources, influencing factors, transmission paths and results of risks, forming a risk system framework and a transmission path, and providing references for risk management and prevention.

In step 3.4, the risk system framework and the propagation path are presented in the form of a chart or text, and the following steps can be adopted: determining the range and the target of a risk system framework, and selecting one or more risk events as analysis objects, such as reservoir dam break, debris flow, flood and the like, according to research problems and purposes; collecting and arranging risk related data and information, acquiring risk occurrence probability, influence degree, related factors, propagation mechanism and other data and information by using methods such as historical data, expert experience, literature data, field investigation and the like, checking the validity and consistency of the data, and processing missing values, abnormal values and the like; identifying and analyzing elements and relations of risks, identifying sources, influencing factors, propagation paths, consequences and other elements of the risks by using methods such as correlation analysis, causal analysis, system analysis and the like, analyzing co-causation relations and mutual induction mechanisms among the risk elements, and determining the structure and rules of the risks; establishing and drawing a risk system frame and a propagation path, and establishing and drawing a chart of the risk system frame and the propagation path, such as a risk tree, a risk matrix, a risk map, a risk network and the like, according to the risk elements and the relations by using a graphic tool or software, or setting forth the content and logic of the risk system frame and the propagation path by using a text description mode; verifying and optimizing the risk system framework and the propagation path, verifying and optimizing the rationality and the effectiveness of the risk system framework and the propagation path by using methods such as sensitivity analysis, scene analysis, simulation analysis and the like, checking the response and the adaptability of the risk system framework and the propagation path to different parameter changes and situation changes, and proposing improvement and perfection.

Further, step 5 includes the following steps.

And according to the risk evaluation result, determining the possibility and the result of the risk, analyzing the influence range and the hazard degree of the risk, and determining the management priority and the emergency response level of the risk. The purpose of this step is to sort and order the risks in order to formulate appropriate risk management and emergency plans. Common methods are risk matrix methods and risk map methods.

And selecting proper risk management and control measures and emergency plan types, and corresponding evaluation models, tools and indexes according to the characteristics and evaluation purposes of the risk. The purpose of this step is to adopt different methods and means according to different situations of risks, so as to achieve the effect of reducing risks or coping with risks. According to the source, property, controllability and the like of risks, proper risk management measures such as risk avoidance, risk transfer, risk alleviation, risk bearing and the like are selected, and the selection of the risk management measures needs to consider factors such as cost and income of the risks, acceptable degree of the risks and the like. And selecting proper emergency plan types, such as comprehensive emergency plans, special emergency plans, field emergency plans and the like, according to the influence range, the hazard degree, the emergency requirements and the like of risks. The selection of the emergency plan type needs to consider the factors of emergency targets, principles, organizations, programs, resources and the like. And selecting proper evaluation models, tools and indexes, such as a risk evaluation model, a risk evaluation tool, a risk evaluation index and the like, according to the characteristics and the evaluation purpose of the risk. The selection of the evaluation model, tool and index needs to consider the feasibility, effectiveness, scientificity and other factors of the evaluation.

And establishing a risk management and control measure and emergency plan index system, wherein the risk management and control measure and emergency plan index system comprises a risk identification index, a risk analysis index, a risk evaluation index, a risk control index, a risk emergency index, and a relation and logic between indexes. The purpose of this step is to quantify and evaluate the effects of risk management measures and emergency protocols for ease of supervision and improvement. The risk identification index is used for describing existence and characteristics of risks, such as occurrence frequency of risk events, number of risk factors, type of risk and the like. Risk analysis indicators are used to describe the cause and impact of risk, such as the weight of risk factors, the scope of risk impact, the path of risk propagation, etc. The risk assessment index is used to describe the level and type of risk, such as risk value, risk index, risk level, risk category, etc. The risk control index is used to describe implementation and effect of risk management measures, such as cost of risk control, benefit of risk control, efficiency of risk control, satisfaction of risk control, and the like. The risk emergency indicators are used to describe the implementation and effectiveness of the emergency protocol, such as the time of emergency response, the quality of emergency treatment, the speed of emergency recovery, the accuracy of emergency assessment, and the like. The relationships and logic between the metrics are used to describe the structure and function of the metric system, such as the level of the metrics, the weights of the metrics, the computing method of the metrics, the evaluation criteria of the metrics, and so on.

And determining the weight, the threshold value and the grading parameters of the risk management and control measures and the emergency plan, namely, giving corresponding weight to each index, sorting and prioritizing according to the importance and urgency of the risk, and setting acceptable range of the risk and grading standard of the risk grade. The purpose of this step is to optimize and adjust the risk management measures and emergency plans to improve the effect of risk management. According to the importance and sensitivity of the indexes, corresponding weights are given to each index, and the effect and influence of the indexes in risk management are reflected. The weight can be determined by subjective or objective methods, such as expert scoring, analytic hierarchy process, entropy method, gray correlation method, etc. And setting corresponding thresholds for each index according to the acceptable degree and the tolerance degree of the risk, and reflecting the normal and abnormal states and ranges of the indexes. The threshold value may be determined empirically or statistically, such as historical averages, standard deviations, confidence intervals, quantiles, etc. The threshold value may be determined by subjective or objective methods, such as risk preference, risk tolerance, risk criteria, and the like. And (3) determining grading parameters: and setting corresponding grading parameters for each risk according to the management priority and the emergency response level of the risk, and reflecting the severity and the emergency of the risk. The determination of the grading parameters may be performed by qualitative or quantitative methods, such as risk matrix, risk map, risk score, etc.

And (3) managing and controlling risks and compiling an emergency plan, namely, formulating corresponding managing and controlling measures and emergency treatment programs for each risk according to the selected managing and controlling measures and plan types to obtain the managing and controlling modes and the emergency plan of the risks. The purpose of this step is to implement and perform risk management to achieve the goal of reducing or coping with risk. Programming a risk management and control scheme: according to the grade and type of the risk, proper risk management measures such as risk avoidance, risk transfer, risk alleviation, risk bearing and the like are selected, and targets, responsibilities, resources, time, cost, effects and the like of risk management are defined to form a risk management scheme such as a risk control plan, a risk control measure list, a risk control responsibility matrix and the like. Programming an emergency plan: according to the grade and type of the risk, a proper emergency plan type is selected, such as a comprehensive emergency plan, a special emergency plan, a site emergency plan and the like, and the targets, principles, organizations, programs, resources, evaluations and the like of the emergency plan are defined to form an emergency plan, such as an emergency response flow chart, an emergency treatment measure list, an emergency resource list, an emergency evaluation list and the like.

Further, step 6 includes the following steps.

In step 6.3, according to the risk management performance evaluation report, the advantage and the deficiency of risk management are analyzed to evaluate the effect and the value of risk management and find the problem and the vulnerability of risk management, and the common methods include a SWOT analysis method, a cost benefit analysis method and a balanced score card method. The problem and reason for risk management are found out for diagnosing defects and disorders of risk management, and analyzing root causes and influencing factors of risk management, and common methods are a problem tree analysis method, a fish bone map analysis method and a 5W2H analysis method. The direction and goal of improvement of risk management are determined in order to formulate improvement measures and plans for risk management, and to define desired results and evaluation criteria for risk management.

In step 6.4, measures and advice for improving risk management are provided for the purpose of providing specific measures and advice for improving the effect and value of risk management according to the direction and goal of improvement of risk management. The purpose of the risk management improvement is to integrate the measures and suggestions for improving risk management into one complete improvement for implementation and execution.

Determining indexes of risk management performance evaluation, and selecting proper indexes according to four dimensions; these four dimensions are finance, customers, internal processes and learning and growth, reflecting the results, impact, efficiency and effect of risk management, respectively. There should be several specific metrics for each dimension, such as: financial dimension: risk loss rate, risk-adjusted yield, risk capital return rate, etc.; customer dimension: risk management satisfaction, risk management trust, risk management loyalty, etc.; internal flow dimension: risk identification coverage rate, risk assessment accuracy rate, risk coping timeliness rate and the like; learning and growth dimensions: risk management knowledge level, risk management innovation capability, risk management cultural atmosphere, and the like.

And (5) giving the weight of each dimension and each index by adopting an expert scoring method. The method is a commonly used multi-attribute decision method, by inviting some expert knowledge personnel to score the importance of each dimension and each index, and then calculating the weight of each dimension and each index according to a certain algorithm. The sum of the weights should be 1 reflecting the relative proportions of the dimensions and indices in the risk management performance assessment.

And a five-level evaluation method is adopted to give the standards of the quality, the good quality, the medium quality, the poor quality and the inferior quality of each index. The five-level evaluation method is a simple evaluation method, and evaluates the actual performance of each index by setting five-level division criteria for each index.

The scores of the quality, the good, the middle, the bad and the inferior of each index are given by adopting a percentage system. The percentile is a method of converting the evaluation result of each index into a numerical value, and the actual performance of each index is scored by setting the scores of five levels of each index.

And calculating the total score of the risk management performance evaluation, namely the comprehensive evaluation value of the risk management, and calculating the total score of the risk management performance evaluation according to the weights and the scores of the dimensions and the indexes. And calculating the comprehensive evaluation value of risk management in a weighted average mode. For example, if the weight of the financial dimension is 0.4, the weight of the customer dimension is 0.3, the weight of the internal process dimension is 0.2, and the weight of the learning and growth dimension is 0.1, then the total score for risk management performance assessment can be expressed as: total score = 0.4 x financial dimension score +0.3 x customer dimension score +0.2 x internal process dimension score +0.1 x learning and growth dimension score. The total score ranges from 20-100, with higher values indicating better risk management performance.

In order to verify the effectiveness of the hydraulic engineering quality safety risk assessment method, hydraulic engineering A, hydraulic engineering B and hydraulic engineering C are selected as cases.

The hydraulic engineering A is a key hydraulic engineering, and relates to functions of water storage, flood discharge, power generation and the like of a reservoir, and also relates to benefits of downstream flood control, irrigation, ecology and the like. The risk assessment of the engineering adopts the hydraulic engineering quality safety risk assessment method of the application, and the risks in the engineering design, construction, operation and other stages are comprehensively identified, evaluated and controlled. According to the risk assessment result, the overall risk level of the project is medium, and main risk factors comprise: complicated geological conditions, unstable construction quality, imperfect flood discharge facilities, large reservoir water level change, dense downstream manholes and the like. Corresponding risk management measures and emergency plans are formulated for the risk factors, and the corresponding risk management measures and emergency plans comprise: enhancing geological investigation and monitoring, improving construction quality management level, perfecting flood discharging facilities and schemes, reasonably adjusting reservoir water level, enhancing downstream flood control propaganda and rescue, and the like. By implementing the measures and the plans, the risk level of the engineering is effectively reduced, the quality and the safety level of the engineering are improved, and the smooth completion and operation of the engineering are ensured. According to the risk management performance evaluation, the risk identification rate of the project is 95%, the risk control rate is 90%, the risk disposal rate is 85%, the risk loss rate is 5%, the risk management cost benefit ratio is 1.2, and the risk management performance evaluation is always divided into 88 points, so that the excellent level is achieved.

The hydraulic engineering B is an ecological restoration engineering, and aims to improve the water quality, water quantity, water scenery and the like of a river channel, and meanwhile, the hydraulic engineering B also relates to benefits of residents, agriculture, travel and the like along the coast. The risk assessment of the engineering adopts the hydraulic engineering quality safety risk assessment method of the application, and the risks in the planning, construction, operation and other stages of the engineering are comprehensively identified, evaluated and controlled. According to the risk assessment result, the overall risk level of the project is low, and main risk factors include: the river hydrologic condition changes, the influence of engineering construction on the environment, the influence of engineering operation on the river ecology, the benefit conflict of coastal residents and the like. Corresponding risk management measures and emergency plans are formulated for the risk factors, and the corresponding risk management measures and emergency plans comprise: the river hydrologic monitoring and prediction is enhanced, environment-friendly construction materials and technology are adopted, river ecology monitoring and protection are implemented, and benefits and demands of coastal residents are coordinated. By implementing the measures and the plans, the risk level of the engineering is effectively reduced, the quality and the safety level of the engineering are improved, and the smooth completion and operation of the engineering are ensured. According to the risk management performance evaluation, the risk identification rate of the project is 98%, the risk control rate is 95%, the risk disposal rate is 90%, the risk loss rate is 2%, the risk management cost benefit ratio is 1.5, and the risk management performance evaluation is totally divided into 92 points, so that the excellent level is achieved.

The hydraulic engineering C is an agricultural hydraulic engineering, and aims to improve the irrigation efficiency and the irrigation benefit of a irrigated area, and relates to the aspects of water resources, soil, crops and the like of the irrigated area. The risk assessment of the engineering adopts the hydraulic engineering quality security risk assessment method of the application, and the risks in the engineering design, construction, management and other stages are comprehensively identified, evaluated and managed. According to the risk assessment result, the overall risk level of the project is medium, and main risk factors comprise: instability of irrigation water sources, aging of irrigation facilities, irregularities in irrigation management, influence of irrigation on the environment, and the like. Corresponding risk management measures and emergency plans are formulated for the risk factors, and the corresponding risk management measures and emergency plans comprise: enhancing the dispatching and the guarantee of irrigation water sources, updating and maintaining irrigation facilities, standardizing and optimizing irrigation management, reducing and controlling the influence of irrigation on the environment and the like. By implementing the measures and the plans, the risk level of the engineering is effectively reduced, the quality and the safety level of the engineering are improved, and the smooth completion and operation of the engineering are ensured. According to the risk management performance evaluation, the risk identification rate of the project is 96%, the risk control rate is 92%, the risk disposal rate is 88%, the risk loss rate is 4%, the risk management cost benefit ratio is 1.3, and the risk management performance evaluation is totally divided into 90 points, so that the excellent level is achieved.

Claims

1. A hydraulic engineering quality safety risk assessment method is characterized by comprising the following steps:

Step 1, collecting various data in the hydraulic engineering construction process, including data in engineering design, construction, materials, equipment, environment and personnel, preprocessing the collected data and constructing a hydraulic engineering risk database;

step 2, analyzing data in a hydraulic engineering risk database, and identifying potential risk factors and risk events and relations between the potential risk factors and the risk events;

Step 3, constructing a risk system framework reflecting risk logic association through risk evaluation and risk event association analysis, and providing basis for subsequent risk management;

Step 4, selecting proper risk evaluation methods and standards according to different risk types, levels and grades, establishing a risk evaluation index system, determining the weight, threshold and grading parameters of risk evaluation, carrying out quantitative or descriptive evaluation on the risk, and outputting a risk evaluation result and a report;

step 5, according to the risk evaluation result, formulating targeted safety control measures and emergency plans, including prevention, control, transfer and bearing of risks, and monitoring, reporting, disposal and recovery flows of risks;

2. The method for evaluating the quality and safety risk of hydraulic engineering according to claim 1, wherein the specific steps of constructing a hydraulic engineering risk database are as follows:

Determining the purpose, range, function and user requirement of a hydraulic engineering risk database, and the source, type, format, quality and safety requirement of data;

According to the result of the demand analysis, designing a data structure of a hydraulic engineering risk database, namely an organization mode and a storage mode of data;

According to the result of the data structure design, a data model of a hydraulic engineering risk database is designed, namely, the logic representation and the conceptualization of data are realized;

According to the result of the data model design, formulating a data element standard of a hydraulic engineering risk database, namely, the specification of the minimum unit and the basic element of the data;

according to the result of the data element standard establishment, a data dictionary management system of the hydraulic engineering risk database is established, namely, the description and annotation management of the data are carried out;

3. The hydraulic engineering quality safety risk assessment method according to claim 1, wherein the step 2 comprises the following steps:

Step 2.1, performing basic descriptive statistical analysis on data in a hydraulic engineering risk database, including calculating an average value, a standard deviation, a maximum value, a minimum value, a frequency and a percentage of the data to know basic distribution and characteristics of the data;

Step 2.2, carrying out association analysis on the data in the hydraulic engineering risk database to find out relativity and causality in the data, thereby identifying potential risk factors and risk events and the relationship between the potential risk factors and the risk events;

Step 2.3, carrying out cluster analysis on the data in the hydraulic engineering risk database to divide the data into a plurality of similar subsets or categories, thereby identifying different risk types and risk grades;

Step 2.4, carrying out classification analysis on the data in the hydraulic engineering risk database to establish a classification model or a prediction model of the data, so as to identify influence factors and influence degrees of risks, and occurrence probability and consequences of the risks;

Step 2.5, carrying out regression analysis on the data in the hydraulic engineering risk database to establish a regression model or a fitting model of the data, thereby identifying the change trend and the change rule of the risk, and the influence factors and the influence degree of the risk;

Step 2.6, carrying out time sequence analysis on the data in the hydraulic engineering risk database to analyze the time sequence characteristics and the time sequence modes of the data, thereby identifying the periodicity, the seasonality, the trending and the randomness of the risk, and the development trend and the prediction result of the risk;

4. The hydraulic engineering quality safety risk assessment method according to claim 1, wherein the step 3 comprises the following steps:

According to the occurrence probability and the influence degree of the risk, quantitatively or qualitatively evaluating the risk by adopting a proper risk evaluation method, and calculating a risk value or a risk index;

dividing risks into different types, grades and grades according to risk evaluation results;

Determining a co-cause relation and a mutual induction mechanism between risk events by using a correlation analysis method, and analyzing sources, influencing factors, propagation paths and consequences of risks to form a risk system framework and a propagation path;

5. The method for evaluating the quality and safety risk of the hydraulic engineering according to claim 1, wherein a risk evaluation index system is established, and weights, thresholds and grading parameters of risk evaluation are determined, specifically:

Selecting proper evaluation indexes and corresponding quantized or descriptive index values according to the characteristics and the evaluation purposes of the hydraulic engineering;

quantitatively weighting the evaluation index by using an analytic hierarchy process to reflect the importance of the index;

6. The method for evaluating the quality and safety risk of the hydraulic engineering according to claim 1, wherein the risk is quantitatively or descriptively evaluated, and a risk evaluation result and report are output, specifically:

calculating or analyzing the risk according to the selected evaluation method to obtain the value or grade of the risk;

combining the analysis theory to comprehensively evaluate the risks of single index or multiple indexes to obtain the overall risk level of the engineering;

7. The hydraulic engineering quality safety risk assessment method according to claim 1, wherein the step 5 comprises the following steps:

According to the risk evaluation result, determining the possibility and the result of the risk, analyzing the influence range and the hazard degree of the risk, and determining the management priority and the emergency response level of the risk;

According to the characteristics and the evaluation purposes of risks, proper risk management and control measures and emergency plan types, and corresponding evaluation models, tools and indexes are selected;

Establishing a risk management and control measure and emergency plan index system, wherein the risk management and control measure and emergency plan index system comprises a risk identification index, a risk analysis index, a risk evaluation index, a risk control index, a risk emergency index, and a relation and logic between indexes;

determining weights, thresholds and grading parameters of risk management and control measures and emergency plans, namely giving corresponding weights to each index, sorting and prioritizing according to importance and urgency of risks, and setting acceptable ranges of risks and grading standards of risk grades;

The risk is managed and controlled and an emergency plan is compiled, namely corresponding management and control measures and emergency treatment programs are formulated for each risk according to the selected management and control measures and plan types, and the management and control scheme and the emergency plan of the risk are obtained;

8. The hydraulic engineering quality safety risk assessment method according to claim 1, wherein the step 6 comprises the following steps:

Step 6.1, establishing a risk management performance evaluation index system: determining indexes of risk management performance assessment, including risk identification rate, risk control rate, risk disposal rate, risk loss rate, risk management cost benefit ratio, and corresponding weights, standards and methods according to targets, contents, processes and results of risk management;

Step 6.2, periodically developing risk management performance assessment: according to the risk management performance evaluation index system, related data and information of risk management are collected, arranged and analyzed regularly, scores of various indexes are calculated, the effect and efficiency of risk management are comprehensively evaluated, and a risk management performance evaluation report is output;

Step 6.3, analyzing the advantages and disadvantages of risk management: analyzing the advantages and the disadvantages of risk management according to the risk management performance evaluation report, finding out the problems and reasons of the risk management, and determining the improvement direction and the aim of the risk management;

step 6.4, improvement measures and suggestions are provided: according to the improvement direction and the aim of risk management, providing measures and suggestions for improving the risk management, including perfecting a risk management system, optimizing a risk management flow, improving the risk management capability and enhancing the risk management culture, and forming a risk management improvement scheme;

9. The method for evaluating the quality and safety risk of hydraulic engineering according to claim 8, wherein in step 6.1, a hierarchical analysis method is adopted for establishing a risk management performance evaluation index system, and the specific steps are as follows:

Dividing the problem of risk management performance evaluation into a target layer, a criterion layer and a scheme layer, wherein the target layer is risk management performance evaluation, the criterion layer is an index of risk management performance evaluation, and the scheme layer is an object of risk management performance evaluation;

For each layer, the relative importance between the factors is given using expert scoring: a scale of 1-9 is adopted, wherein 1 represents that two factors are equally important, 9 represents that one factor is extremely important than the other factor, and the middle number represents importance of different degrees; constructing a judgment matrix A= _m×m according to the scoring, wherein a _ij represents the importance of the ith factor relative to the jth factor, and m represents the number of factors;

For each judgment matrix, solving a weight vector W of each factor by using a eigenvalue method, wherein W _i represents the weight of the ith factor and satisfies W _i≥0,w₁+w₂…+w_i…+w_m =1;

For each judgment matrix, the consistency ratio CR is calculated by utilizing the consistency index CI and the average random consistency index RI, the consistency of the judgment matrix is checked, and the CR is less than 0.1, otherwise, the judgment matrix is required to be modified, and the specific formula is as follows: CI=/, wherein lambda _max is the maximum eigenvalue of the decision matrix and n is the order of the decision matrix; RI is a constant corresponding to the difference in n, wherein: when n=1, ri=0; when n=2, ri=0; when n=3, ri=0.58; when n=4, ri=0.9; when n=5, ri=1.12; when n=6, ri=1.24; when n=7, ri=1.32; when n=8, ri=1.41; when n=9, ri=1.45; when n=10, ri=1.49; CR=CI/RI, if CR is less than 0.1, the consistency of the judgment matrix is accepted, otherwise, the judgment matrix needs to be modified;

10. The method for evaluating the quality and safety risk of hydraulic engineering according to claim 8, wherein in step 6.2, a balanced score card algorithm is adopted to evaluate risk management performance, and the specific steps are as follows:

determining targets for risk management performance assessment, including reducing risk loss, improving risk control capability, optimizing risk management processes, and improving risk management levels;

Determining indexes of risk management performance evaluation, and selecting proper indexes according to four dimensions;

The weight of each dimension and each index is given by adopting an expert scoring method;

a five-level evaluation method is adopted to give the standards of the quality, the good quality, the medium quality, the bad quality of each index;

the scores of the quality, the well, the middle, the poor and the inferior of each index are given by adopting a percentile;