Title | ||
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Causality Analysis Between Soil Of Different Depth Moisture And Precipitation In The United States |
Abstract | ||
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Previously the stronger coupling between soil moisture and precipitation in the land-atmosphere interaction have widely been studied. However, few work discusses the causality between them. In this paper, we use Granger causality (GC) and New causality (NC) to detect the causality between soil of different depth moisture and precipitation. Our results demonstrate that the causality between shallow soil moisture and precipitation is greater than that between deep soil moisture and precipitation. And the results also demonstrate that the NC method is much clearer to reveal the causal influence between soil moisture and precipitation than GC method in the time domain. |
Year | DOI | Venue |
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2017 | 10.1007/978-3-319-70139-4_58 | NEURAL INFORMATION PROCESSING, ICONIP 2017, PT V |
Keywords | Field | DocType |
Granger causality, New causality, Soil moisture, Precipitation | Soil science,Moisture,Causality,Pattern recognition,Computer science,Granger causality,Artificial intelligence,Water content,Precipitation | Conference |
Volume | ISSN | Citations |
10638 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 2 | 7 |
Name | Order | Citations | PageRank |
---|---|---|---|
Hui Su | 1 | 293 | 33.30 |
Sanqing Hu | 2 | 452 | 42.72 |
Tong Cao | 3 | 0 | 0.68 |
Jianhai Zhang | 4 | 13 | 5.32 |
Yuying Zhu | 5 | 0 | 0.68 |
Bocheng Wang | 6 | 0 | 0.68 |
Lan Jiang | 7 | 23 | 3.54 |