The Implementation Effect of Chinese Soil and Water Conservation Law in Pisha Stone Area Use SPSS Analyses Big Data

Minglei Kang; Binbin Li; Yanshuang Zheng; Feifei Dong; Zhan Zhang; Yuanyuan Chang; Liting Hou; Haibin Zhao; Cheng Chen; Yang Liu; Huiling Duan; Maolin Li; Zhenzhou Shen

doi:10.2991/978-94-6463-064-0_79

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The Implementation Effect of Chinese Soil and Water Conservation Law in Pisha Stone Area Use SPSS Analyses Big Data

Authors

Minglei Kang¹, Binbin Li²^{, 2}^{, *}, Yanshuang Zheng³, Feifei Dong³, Zhan Zhang⁴, Yuanyuan Chang⁴, Liting Hou⁵, Haibin Zhao⁵, Cheng Chen⁵, Yang Liu³, Huiling Duan³, Maolin Li³, Zhenzhou Shen³

¹North Henan Water Conservancy Engineering Administration, Xinxiang, 450000, China

²Water and Soil Conservation Monitoring Center of Ministry of Water Resources, Beijing, 100053, China

³Yellow River Institute of Hydraulic Research, Zhengzhou, 450003, China

⁴Yellow River Institute of Hydrology and Water Resources, Zhengzhou, 450003, China

⁵Yellow River Conservancy Technical College, Kaifeng, 450003, Henan, China

^*Corresponding author. Email: libinbin@wrm.gov.cn

Corresponding Author

Binbin Li

Available Online 27 December 2022.

DOI: 10.2991/978-94-6463-064-0_79 How to use a DOI?
Keywords: SPSS; Chinese Soil and Water Conservation Law; Pisha Stone Area
Abstract: The soil and water loss is very serious in Pisha stone area of Yellow River basin, which is called the “ecological cancer of the Earth”. The area covers only 1.67 × 103 km², but the coarse sediment produced by the area accounts for 25% of the silt deposited in the lower Yellow River. We used SPSS data analysis software to calculate the amount of soil and water loss in the Arsenic sandstone area of the Yellow River basin in the past few years, and found that the soil and water loss in this area is very serious. The data shows: the control plot compared with natural plot, the runoff decreased from 41% in the initial stage to more than 72%, and the sediment yield decreased from 61% to more than 90%. The runoff reduction benefit of the maximum rainfall on 13 August 2020 was 72%, and the sediment reduction benefit reached more than 89%. This paper can play a scientific and technological support role in further promoting the implementation of Soil and Water Conservation Law of the People’s Republic of China in Pisha area.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
Series: Atlantis Highlights in Computer Sciences
Publication Date: 27 December 2022
ISBN: 10.2991/978-94-6463-064-0_79
ISSN: 2589-4900
DOI: 10.2991/978-94-6463-064-0_79 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Minglei Kang
AU  - Binbin Li
AU  - Yanshuang Zheng
AU  - Feifei Dong
AU  - Zhan Zhang
AU  - Yuanyuan Chang
AU  - Liting Hou
AU  - Haibin Zhao
AU  - Cheng Chen
AU  - Yang Liu
AU  - Huiling Duan
AU  - Maolin Li
AU  - Zhenzhou Shen
PY  - 2022
DA  - 2022/12/27
TI  - The Implementation Effect of Chinese Soil and Water Conservation Law in Pisha Stone Area Use SPSS Analyses Big Data
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 768
EP  - 775
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_79
DO  - 10.2991/978-94-6463-064-0_79
ID  - Kang2022
ER  -

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