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Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms
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Key Laboratory of Comprehensive and Highly Efficient Utilization of Salt Lake Resources, Qinghai Institute of Salt Lakes, Chinese Academy of Sciences, Xining 810008, China
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Publication type: Journal Article
Publication date: 2025-04-01
scimago Q1
wos Q1
SJR: 1.323
CiteScore: 7.4
Impact factor: 5.0
ISSN: 22145818
Abstract
Study regionQarhan Salt Lake, the largest salt lake in China, located in the Qaidam Basin.
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Yu D. et al. Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms // Journal of Hydrology: Regional Studies. 2025. Vol. 58. p. 102195.
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Yu D., Wang Z., Yue C., Wang J. Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms // Journal of Hydrology: Regional Studies. 2025. Vol. 58. p. 102195.
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TY - JOUR
DO - 10.1016/j.ejrh.2025.102195
UR - https://linkinghub.elsevier.com/retrieve/pii/S2214581825000199
TI - Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms
T2 - Journal of Hydrology: Regional Studies
AU - Yu, Dongmei
AU - Wang, Zitao
AU - Yue, Chao
AU - Wang, Jianping
PY - 2025
DA - 2025/04/01
PB - Elsevier
SP - 102195
VL - 58
SN - 2214-5818
ER -
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@article{2025_Yu,
author = {Dongmei Yu and Zitao Wang and Chao Yue and Jianping Wang},
title = {Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms},
journal = {Journal of Hydrology: Regional Studies},
year = {2025},
volume = {58},
publisher = {Elsevier},
month = {apr},
url = {https://linkinghub.elsevier.com/retrieve/pii/S2214581825000199},
pages = {102195},
doi = {10.1016/j.ejrh.2025.102195}
}