Identification of Soil Moisture–Precipitation Feedback Based on Temporal Information Partitioning Networks
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作者:
Lou, Wei
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机构:
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, ChinaState Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China
Lou, Wei
[1
]
Liu, Pan
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机构:
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, ChinaState Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China
Liu, Pan
[1
]
Cheng, Lei
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h-index: 0
机构:
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, ChinaState Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China
Cheng, Lei
[1
]
Li, Zejun
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h-index: 0
机构:
Guangdong Research Institute of Water Resources and Hydropower, Guangzhou, ChinaState Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China
Li, Zejun
[2
]
机构:
[1] State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China
[2] Guangdong Research Institute of Water Resources and Hydropower, Guangzhou, China
来源:
Journal of the American Water Resources Association
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2022年
/
58卷
/
06期
关键词:
Compilation and indexing terms;
Copyright 2024 Elsevier Inc;
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摘要:
American waters - Feed-back based - Granger Causality - Hydrologic cycles - Illinois - Land-atmosphere feedback - Nonlinear granger causality - Partitioning networks - Temporal information - Waters resources