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

文献类型：期刊论文

作者Feng, Ting1,2,3,4; Zhu, Shuzhen1,2,3,4; Huang, Farong1,2,4,5; Hao, Jiansheng6; Mind'je, Richard1,3,7; Zhang, Jiudan1,3; Li, Lanhai1,2,3,4,5
刊名HYDROLOGICAL PROCESSES
出版日期2022-08-01
卷号36期号:8页码:15
关键词machine learning middle Tianshan Mountains regression model snow density spatial variability
ISSN号0885-6087
DOI10.1002/hyp.14644
通讯作者Huang, Farong(huangfr@ms.xjb.ac.cn) ; Li, Lanhai(lilh@ms.xjb.ac.cn)
英文摘要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 < 0.05) with elevation during the accumulation and stable periods. In addition to elevation, latitude and ground surface temperature also had critically impacted the spatial variability of snow density in the study area. In the current study, the machine learning models, especially RF, performed better than MLR for simulating snow density in the three periods. Based on the key environmental variables identified by the machine learning model and correlation analysis, this study also provides practical MLR equations to estimate the spatial variance of snow density during different snow periods in the middle Tianshan Mountains. This method can be used for regional snow mass and snow water equivalent prediction, leading to a better understanding of local snow resources.
WOS关键词TEMPORAL VARIABILITY ; WATER EQUIVALENT ; COVER ESTIMATION ; RANDOM FOREST ; TIEN-SHAN ; DEPTH
资助项目National Natural Science Foundation of China[41901048] ; National Natural Science Foundation of China[U1703241] ; National Cryosphere Desert Data Center[2021kf02] ; National Project of Investigation of Basic Resources for Science and Technology[2017FY100501] ; Youth Innovation Promotion Association of Chinese Academy of Sciences[2021438]
WOS研究方向Water Resources
语种英语
WOS记录号WOS:000833767300001
出版者WILEY
资助机构National Natural Science Foundation of China ; National Cryosphere Desert Data Center ; National Project of Investigation of Basic Resources for Science and Technology ; Youth Innovation Promotion Association of Chinese Academy of Sciences
源URL[http://ir.igsnrr.ac.cn/handle/311030/181157]  
专题中国科学院地理科学与资源研究所
通讯作者Huang, Farong; Li, Lanhai
作者单位1.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi, Peoples R China
2.Chinese Acad Sci, Ili Stn Watershed Ecosyst Res, Xinyuan, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
4.Xinjiang Key Lab Water Cycle & Utilizat Arid Zone, Urumqi, Peoples R China
5.Chinese Acad Sci, Res Ctr Ecol & Environm Cent Asia, Urumqi, Peoples R China
6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing, Peoples R China
7.Univ Lay Adventists Kigali UNILAK, Fac Environm Sci, Kigali, Rwanda
推荐引用方式
GB/T 7714		 Feng, Ting,Zhu, Shuzhen,Huang, Farong,et al. Spatial variability of snow density and its estimation in different periods of snow season in the middle Tianshan Mountains, China[J]. HYDROLOGICAL PROCESSES,2022,36(8):15.
APA Feng, Ting.,Zhu, Shuzhen.,Huang, Farong.,Hao, Jiansheng.,Mind'je, Richard.,...&Li, Lanhai.(2022).Spatial variability of snow density and its estimation in different periods of snow season in the middle Tianshan Mountains, China.HYDROLOGICAL PROCESSES,36(8),15.
MLA Feng, Ting,et al."Spatial variability of snow density and its estimation in different periods of snow season in the middle Tianshan Mountains, China".HYDROLOGICAL PROCESSES 36.8(2022):15.

入库方式： OAI收割

来源：地理科学与资源研究所

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