Spatial variability of snow density and its estimation in different periods of snow season in the middle Tianshan Mountains, China

• Published in: Hydrological processes 2022-08, Vol.36 (8), p.n/a
• Main Authors: Feng, Ting, Zhu, Shuzhen, Huang, Farong, Hao, Jiansheng, Mind'je, Richard, Zhang, Jiudan, Li, Lanhai
• Format: Article
• Language: English
• Subjects: Accumulation; Correlation analysis; Density; Elevation; Learning algorithms; Machine learning; middle Tianshan Mountains; Modelling; Mountainous areas; Mountains; Oases; regression model; Regression models; Seasons; Snow; Snow density; Snow-water equivalent; Snowpack; Spatial analysis; Spatial variability; Spatial variations; Surface temperature; Variability
• ISSN: 0885-6087; 1099-1085
• DOI: 10.1002/hyp.14644

Snow density is an essential property of snowpack. To obtain the spatial variability of snow density and estimate it in different periods of the snow season remain challenging, particularly in the mountainous area. This study analysed the spatial variability of snow density with in‐situ measurements in three different periods (i.e., accumulation, stable and melt periods) of the snow seasons of 2017/2018 and 2018/2019 in the middle Tianshan Mountains, China. The simulation performances of the multiple linear regression (MLR) model and three machine learning (random forest [RF], extreme gradient boosting [XGB] and light gradient boosting machine [LGBM]) models were evaluated. Results showed that snow density in the melt period (0.27 g cm−3) was generally greater than that in the stable (0.20 g cm−3) and accumulation periods (0.18 g cm−3), and the spatial variability of snow density in the melt period was slightly smaller compared to that in other two periods. The snow density in the mountainous areas was generally higher than that in the plain or oasis areas. It increased significantly (p