干旱区生态环境知识资源中心(Arid): Identifying and mapping the spatial distribution of regions prone to snowmelt flood hazards in the arid region of Central Asia: A case study in Xinjiang, China

Arid

DOI	10.1111/jfr3.12947
	Identifying and mapping the spatial distribution of regions prone to snowmelt flood hazards in the arid region of Central Asia: A case study in Xinjiang, China
	Liu, Yan; Zhang, Jun Min; Huo, Hong; Li, Yang; Lu, Xin Yu; Wang, Ni; Yang, Yun
通讯作者	Liu, Y
来源期刊	JOURNAL OF FLOOD RISK MANAGEMENT
ISSN	1753-318X
出版年	2024
卷号	17 期号:1
英文摘要	Snowmelt floods are highly hazardous meteorological disasters that can potentially threaten human lives and property. Hence, snowmelt susceptibility mapping (SSM) plays an important role in flood prevention systems and aids emergency responders and flood risk managers. In this paper, a method of identifying snowmelt flood hazards is proposed, and a large-scale snowmelt flood hazard zonation scheme based on historical recordings and multisource remote sensing data is established. To assess the quality of our approach, the proposed model was tested in the cold and arid region of Xinjiang, China. Overall, 140 historical snowmelt flood events and 27 explanatory factors were selected to construct a geospatial dataset for SSM of the contemporary period. GridSearchCV was used to comprehensively search the candidate parameters from the grid of given parameters obtained with the random forest (RF) algorithm. Then, the geospatial dataset was divided into two subsets: 70% for training and 30% for testing. Next, SSM results were obtained with the RF algorithm using optimized parameters. The results indicate that our optimized RF classifier performs well for the task of SSM, with a high AUC value (0.975) for the test dataset. The validation and analysis suggest that the proposed method can efficiently identify snowmelt flood hazards in undersampled arid areas at a regional scale.
英文关键词	large scale multisource remotely sensed data random forest algorithm snowmelt susceptibility mapping
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:001069821600001
WOS关键词	RANDOM FOREST ; MODEL
WOS类目	Environmental Sciences ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404506
推荐引用方式 GB/T 7714	Liu, Yan,Zhang, Jun Min,Huo, Hong,et al. Identifying and mapping the spatial distribution of regions prone to snowmelt flood hazards in the arid region of Central Asia: A case study in Xinjiang, China[J],2024,17(1).
APA	Liu, Yan.,Zhang, Jun Min.,Huo, Hong.,Li, Yang.,Lu, Xin Yu.,...&Yang, Yun.(2024).Identifying and mapping the spatial distribution of regions prone to snowmelt flood hazards in the arid region of Central Asia: A case study in Xinjiang, China.JOURNAL OF FLOOD RISK MANAGEMENT,17(1).
MLA	Liu, Yan,et al."Identifying and mapping the spatial distribution of regions prone to snowmelt flood hazards in the arid region of Central Asia: A case study in Xinjiang, China".JOURNAL OF FLOOD RISK MANAGEMENT 17.1(2024).