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Causality Analysis Between Soil of Different Depth Moisture and Precipitation in the United States

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10638))

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Abstract

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.

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Acknowledgments

This work was funded by National Natural Science Foundation of China under Grants (Nos. 61473110, 61633010), International Science and Technology Cooperation Program of China, Grant No. 2014DFG12570, Key Lab of Complex Systems Modeling and Simulation, Ministry of Education, China.

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Authors and Affiliations

  1. College of Computer Science, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China

    Hui Su, Sanqing Hu, Tong Cao, Jianhai Zhang & Yuying Zhu

  2. Zhejiang University of Media & Communications, Hangzhou, 310018, Zhejiang, China

    Bocheng Wang

  3. Zhejiang Environmental Monitoring Center, Hangzhou, 310018, Zhejiang, China

    Lan Jiang

Authors
  1. Hui Su
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  2. Sanqing Hu
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  3. Tong Cao
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  4. Jianhai Zhang
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  5. Yuying Zhu
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  6. Bocheng Wang
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  7. Lan Jiang
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Corresponding author

Correspondence to Jianhai Zhang .

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Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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Su, H. et al. (2017). Causality Analysis Between Soil of Different Depth Moisture and Precipitation in the United States. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10638. Springer, Cham. https://doi.org/10.1007/978-3-319-70139-4_58

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  • DOI: https://doi.org/10.1007/978-3-319-70139-4_58

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70138-7

  • Online ISBN: 978-3-319-70139-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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