Climate change would result in the increase of extreme weather events. Correspondingly,the increase in extreme precipitation and rapid urbanization would cause more serious waterlogging problems. To address these challenges,it is necessary to develop an adaptive solution to tackle the potential problems of extreme weather events in the future. Based on the observed meteorological data (period: 19662015) of a sponge city in Xining (Qinghai Province,China) ,we adopted the Pearson-III probabilistic distributions method and the linear trend estimation method to estimate the daily maximum precipitation,as extreme precipitation,of the year of 2065. Furthermore,the Storm Water Management Model (SWMM) was applied to simulate and analyze the urban waterlogging problems under future extreme precipitation events. To cope with the urban waterlogging problems,we put forward some climate adaptation schemes involving the deployment of Low Impact Development (LID) measures and pipe network transformation (PNT) . Specifically,the schemes include local-area LID measures deployment,local-area LID measures deployment with local PNT,whole-area LID measures deployment and whole-area LID measures deployment with full flow PNT. The SWMM model was used to simulate these counter-measures,and the ability of these schemes on coping with the extreme precipitation waterlogging problems was evaluated using the entropy weight method. The evaluation results show that the scheme of whole-area LID measures deployment with full flow PNT would be the most effective measure on handling the city's waterlogging problems. The effect of the whole-area LID measures would be close to the effect of the scheme of local LID measures deployment with local PNT. However,PNT could not store and utilize the rainwater resources. Hence,the scheme of whole-area LID measures deployment should be adopted for managing the challenges of urban extreme precipitation events in the future.