# Research on an Evaluation Method of Snowdrift Hazard for Railway Subgrades
###### Abstract  
The objective of this study is to investigate the potential risks posed by snowdrifts, a prevalent cause of natural disasters in northern China, on railway subgrades, and to assess their risk level. As a wind-driven process of snow migration and redeposition, snowdrifts pose a significant threat to the safety of transportation infrastructures. This study focuses on the Afu Railway in Xinjiang, situated on the northern slopes of the Eastern Tianshan Mountains, where it experiences periodic snowdrifts. We employed a combination of the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation (FCE) to construct an integrated evaluation system for assessing the risk of snowdrift to railway subgrades. The results indicate that subgrade design parameters and regional snowfield conditions are two key metrics affecting the extent of snowdrift disasters, with topography, vegetation coverage, and wind speed also exerting certain impacts. The evaluation method of this study aligns with the results of on-site observations, verifying its accuracy and practicality, thereby providing a solid risk assessment framework for snowdrifts along the railway. The scientific and systematic hazard assessment method of railway subgrades developed in this research provides basic data and theoretical support for future research, and provides a scientific basis for relevant departments to formulate countermeasures, so as to improve the safety and reliability of railway operations. snowdrift; railway subgrade; risk assessment; analytic hierarchy process (AHP); fuzzy comprehensive evaluation (FCE) 2024 14 7247 10.3390/2024 14/2247 10.3390/2024 10.3390/2024 10.  
with red areas representing the most snow-covered days and blue areas representing none, overlaid with railway lines, of which 11.83% are situated in regions with more than 180 snow-covered days. Therefore, an in-depth study of the characteristics of snowdrift along transportation infrastructure and the distribution of related disasters is of significant theoretical and practical importance for disaster prevention, mitigation, and ensuring the safety of transportation operations. Snow disaster assessment and regionalization research has experienced a transformation from qualitative to quantitative analysis, and the assessment accuracy has been continuously improved. Early studies, such as the work of [PERSON] [4], analyzed the number and types of snow days, classified Chinese snow, and put forward the principle of comprehensive assessment. With the development of technology, for example, [PERSON] et al. employed the Normalized Difference Vegetation Index (NDVI) and the Snow Water Equivalent (SWE) as assessment indicators, utilizing a regression analysis to evaluate snow disasters in Mongolia [5]. [PERSON] et al. utilized the PSR method to analyze their proposed snow disaster risk indices. They applied a hierarchical analysis and the entropy weight method in determining indicator weights to identify the area vulnerable to snow disasters [6]. In recent years, scholars have conducted extensive research on the prediction of snowdrift disasters and the evaluation of risk levels, proposing various assessment methods. These include snow disaster level assessment models [7; 8; 9; 10] based on distance functions, multi-indicator comprehensive assessment methods, probabilistic analysis models, and integrated risk assessment systems. For example, [PERSON] [11] used the fuzzy comprehensive evaluation method to evaluate the snow disaster in Nagu, Tibet, and [PERSON] [12] established a snow inversion model to improve the classification accuracy. The application of GIS technology, such as the evaluation model established by [PERSON] [13], provides guiding suggestions for snow disaster prevention.