| With the continuous intensification of global climate change,the frequency and intensity of natural disasters are trending upward.In particular,floods caused by extreme precipitation have brought huge economic losses and severe social impacts on cities or regions.As an important part of public transportation,urban rail transit is more vulnerable to natural disasters such as extreme precipitation and waterlogging due to its low-lying terrain and insufficient drainage capacity.Once attacked by rainstorms,it will cause the suspension of subway,or even endanger the safety of passengers.Thus,it is of great significance to formulate effective climate adaptation strategies for urban rail transit under climate change.On account of the limited investment capacity of local government departments,it is an important research topic for cities to progressively invest in the ability of urban rail transit to cope with extreme precipitation in a planned way.This thesis proposes a decision-making model based on climate change for drainage renovation of urban rail transit,which consists of an optimal renovation sequence model and an optimal investment timing model.Firstly,combining geographic information system and complex network theory,this thesis analyzes the inundation risk and node importance of each station,and then uses multi-criteria decision analysis to determine the optimal renovation sequence.Secondly,real options analysis is used to calculate the value of an option to defer for the renovation project and determine the optimal investment timing.Finally,taking the Beijing Urban Rail Transit as an example,the proposed model is empirically analyzed.Considering the uncertainty of climate change and the complexity of actual situation,the model proposed in this thesis can get the optimal renovation sequence and investment timing for drainage renovation of urban rail transit,which is expected to provide a decision-making tool for urban governments to formulate an optimal plan that strengthens the prevention of flooding disasters. |
