Abstract: Railway water damage disasters are the most frequent,widespread,and harmful events on railway lines.They often cause the longest interruptions to train services.In mountainous areas,due to complex terrain and variable climate,water damage disasters occur frequently,which have a serious impact on the safe transportation of railways.Moreover,traditional manual location selection is time-consuming,laborious and difficult to carry out macroscopic optimization and allocation of regions.To solve the problem of intelligent location selection for railway drainage facilities in mountainous areas,by extracting three-dimensional refined terrain features and based on the DBSCAN density clustering algorithm and principal component analysis (PCA),an intelligent optimization allocation algorithm for drainage facility selection of “spatial clustering-dimension reduction combined” is proposed.Taking a railway in a mountainous area of Hunan province as an example,the location selection of railway drainage facilities is predicted.The results show that the prediction results match the actual culvert locations with an accuracy of 92%.The design of drainage ditches covers high-risk areas.The optimized drainage system can reduce the probability of water accumulation on the roadbed and significantly improve the railway's resistance to water damage.The research results veriy the applicability of the drainage facility location selection method based on this allocation algorithm under complex terrain conditions,providing a useful reference for the location design and optimization of drainage facilities in mountainous railway areas.

Key words: refined terrain features, hydrological analysis, drainage facility location selection, DBSCAN clustering, PCA, SCS-CN model