Risk Analysis And Transfer Of Long Distance Water Diversion Project Operation Safety

Long-distance water diversion project is a large-scale water conservancy project to solve the unbalanced spatial distribution of water resources,which provides a strong support for the social and economic development in water-deficient areas.However,the loss caused by engineering accidents is also huge.Therefore,it is very important to do a good job of risk management in its operation period.Long-distance water diversion project has the engineering characteristics of water conservancy project,but also has the characteristics of large span,long distance and wide influence range,resulting in complex risk factors and difficult to manage.This paper takes the Southto-North Water Diversion Project as an example to analyze the law of risk transmission.The main contents are as follows:(1)On the basis of literature review and field investigation,risk factors are divided into seven categories,and risk factors are preliminarily identified.Delphi expert method is used to determine the safety risk index system of long distance water diversion project operation.(2)The integrated DEMATEL-ISM method is adopted to calculate and analyze the safety risk system model of long-distance water diversion project operation.In consideration of the interaction between risk factors,risk factors are classified into levels and risk transmission paths are determined.(3)Using Arena software,the dynamic transfer model of safety risk in the operation of long-distance water diversion project is established.Taking the risk of flood disaster in node 1,the risk of freezing disaster in node 2 and the risk of water pollution in water source area in node 3 as the initial nodes of the model,the dynamic simulation was carried out to obtain the risk transmission rule.(4)The importance ranking of risk factors that affect the safety of longdistance water diversion project operation is conducted by using the method of entropy weight aggregating multi-dimensional data.The model in Chapter 4 is used to verify the ranking results,and it is found that the ranking results of the importance of risk factors based on the entropy weight aggregation multi-dimensional data are optimal.