IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i18p7632-d414276.html
   My bibliography  Save this article

Teleconnections between Snow Cover Change over Siberia and Crop Growth in Northeast China

Author

Listed:
  • Cong Guan

    (College of Earth Science, Jilin University, Changchun 130061, China
    Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
    Changchun Institute of Technology, Changchun 130012, China)

  • Lingxue Yu

    (Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China)

  • Fengqin Yan

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Shuwen Zhang

    (Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China)

Abstract

Snow cover is a sensitive indicator of climate change, and the variations in snow cover can influence the global climate system and terrestrial water cycling. However, the teleconnections between snow cover changes of the northern hemisphere and the crop growth of Northeast China (NEC) are less documented. In this study, we estimated the correlations between spring snow cover area over Siberia (SSCA) and the regional climate, as well as the crop growth in NEC based on both satellite measurement and observational climate records from 1982 to 2015. The local temperature, including minimum temperature (Tmin) in May–June, maximum temperature (Tmax), and Tmin in July–August, showed significant negative correlations with SSCA. SSCA is found to be negatively correlated to rainfall during the beginning of the growing season, while positively correlated to rainfall during the peak growing season for the agricultural ecosystem of NEC. The remote responses of the normalized difference vegetation index (NDVI) to SSCA varied across different climate zones and different growing periods. The NDVI variations over cold and dry cultivated regions exhibit negative correlations with SSCA in May–June, which is opposite for the wetter areas. The negative correlation between NDVI over the agricultural ecosystem and SSCA during the peak growing season was also detected, implying the variations in SSCA might be an essential driving factor in affecting the crop growth through modifying the regional climate of NEC. In the future, more in situ observations and model simulations should be conducted to verify our results described here, which would have significant implications for maintaining regional food security and sustainable development in Northeast China under the changing climate background.

Suggested Citation

  • Cong Guan & Lingxue Yu & Fengqin Yan & Shuwen Zhang, 2020. "Teleconnections between Snow Cover Change over Siberia and Crop Growth in Northeast China," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7632-:d:414276
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/18/7632/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/18/7632/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shilong Piao & Philippe Ciais & Yao Huang & Zehao Shen & Shushi Peng & Junsheng Li & Liping Zhou & Hongyan Liu & Yuecun Ma & Yihui Ding & Pierre Friedlingstein & Chunzhen Liu & Kun Tan & Yongqiang Yu , 2010. "The impacts of climate change on water resources and agriculture in China," Nature, Nature, vol. 467(7311), pages 43-51, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. He, Liuyue & Xu, Zhenci & Wang, Sufen & Bao, Jianxia & Fan, Yunfei & Daccache, Andre, 2022. "Optimal crop planting pattern can be harmful to reach carbon neutrality: Evidence from food-energy-water-carbon nexus perspective," Applied Energy, Elsevier, vol. 308(C).
    2. Ding, Yimin & Wang, Weiguang & Song, Ruiming & Shao, Quanxi & Jiao, Xiyun & Xing, Wanqiu, 2017. "Modeling spatial and temporal variability of the impact of climate change on rice irrigation water requirements in the middle and lower reaches of the Yangtze River, China," Agricultural Water Management, Elsevier, vol. 193(C), pages 89-101.
    3. Bu, Lingduo & Chen, Xinping & Li, Shiqing & Liu, Jianliang & Zhu, Lin & Luo, Shasha & Lee Hill, Robert & Zhao, Ying, 2015. "The effect of adapting cultivars on the water use efficiency of dryland maize (Zea mays L.) in northwestern China," Agricultural Water Management, Elsevier, vol. 148(C), pages 1-9.
    4. Wenfeng Chi & Yuanyuan Zhao & Wenhui Kuang & Tao Pan & Tu Ba & Jinshen Zhao & Liang Jin & Sisi Wang, 2021. "Impact of Cropland Evolution on Soil Wind Erosion in Inner Mongolia of China," Land, MDPI, vol. 10(6), pages 1-16, June.
    5. Xu, Ying & Findlay, Christopher, 2019. "Farmers’ constraints, governmental support and climate change adaptation: Evidence from Guangdong Province, China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(4), October.
    6. Zhongen Niu & Huimin Yan & Fang Liu, 2020. "Decreasing Cropping Intensity Dominated the Negative Trend of Cropland Productivity in Southern China in 2000–2015," Sustainability, MDPI, vol. 12(23), pages 1-14, December.
    7. Yuhong Shuai & Liming Yao, 2021. "Adjustable Robust Optimization for Multi-Period Water Allocation in Droughts Under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 4043-4065, September.
    8. Zhang, Fengtai & Xiao, Yuedong & Gao, Lei & Ma, Dalai & Su, Ruiqi & Yang, Qing, 2022. "How agricultural water use efficiency varies in China—A spatial-temporal analysis considering unexpected outputs," Agricultural Water Management, Elsevier, vol. 260(C).
    9. Chen, Qi & Qu, Zhaoming & Ma, Guohua & Wang, Wenjing & Dai, Jiaying & Zhang, Min & Wei, Zhanbo & Liu, Zhiguang, 2022. "Humic acid modulates growth, photosynthesis, hormone and osmolytes system of maize under drought conditions," Agricultural Water Management, Elsevier, vol. 263(C).
    10. Kang, Shaozhong & Hao, Xinmei & Du, Taisheng & Tong, Ling & Su, Xiaoling & Lu, Hongna & Li, Xiaolin & Huo, Zailin & Li, Sien & Ding, Risheng, 2017. "Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice," Agricultural Water Management, Elsevier, vol. 179(C), pages 5-17.
    11. Zhihai Yang & Amin W. Mugera & Fan Zhang, 2016. "Investigating Yield Variability and Inefficiency in Rice Production: A Case Study in Central China," Sustainability, MDPI, vol. 8(8), pages 1-11, August.
    12. Xiaoguang Chen & Madhu Khanna & Lu Yang, 2022. "The impacts of temperature on Chinese food processing firms," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(2), pages 256-279, April.
    13. Sicong Wang & Changhai Qin & Yong Zhao & Jing Zhao & Yuping Han, 2023. "The Evolutionary Path of the Center of Gravity for Water Use, the Population, and the Economy, and Their Decomposed Contributions in China from 1965 to 2019," Sustainability, MDPI, vol. 15(12), pages 1-20, June.
    14. Minghao Bai & Shenbei Zhou & Ting Tang, 2022. "A Reconstruction of Irrigated Cropland Extent in China from 2000 to 2019 Using the Synergy of Statistics and Satellite-Based Datasets," Land, MDPI, vol. 11(10), pages 1-27, September.
    15. Yang, Wenjie & Li, Yanhang & Jia, Bingli & Liu, Lei & Yuan, Aijing & Liu, Jinshan & Qiu, Weihong, 2024. "Optimized fertilization based on fallow season precipitation and the Nutrient Expert system for dryland wheat reduced environmental risks and increased economic benefits," Agricultural Water Management, Elsevier, vol. 291(C).
    16. Wang, Guangshuai & Liang, Yueping & Zhang, Qian & Jha, Shiva K. & Gao, Yang & Shen, Xiaojun & Sun, Jingsheng & Duan, Aiwang, 2016. "Mitigated CH4 and N2O emissions and improved irrigation water use efficiency in winter wheat field with surface drip irrigation in the North China Plain," Agricultural Water Management, Elsevier, vol. 163(C), pages 403-407.
    17. Cao, Meng & Chen, Min & Liu, Ji & Liu, Yanli, 2022. "Assessing the performance of satellite soil moisture on agricultural drought monitoring in the North China Plain," Agricultural Water Management, Elsevier, vol. 263(C).
    18. Xu, Zhihao & Yin, Xinan & Yang, Zhifeng & Cai, Yanpeng & Sun, Tao, 2016. "New model to assessing nutrient assimilative capacity in plant-dominated lakes: Considering ecological effects of hydrological changes," Ecological Modelling, Elsevier, vol. 332(C), pages 94-102.
    19. Jian, Yuqing & Liu, Zhengjia & Gong, Jianzhou, 2022. "Response of landscape dynamics to socio-economic development and biophysical setting across the farming-pastoral ecotone of northern China and its implications for regional sustainable land management," Land Use Policy, Elsevier, vol. 122(C).
    20. Xie, Yang & Zilberman, David, 2014. "The Economics of Water Project Capacities and Conservation Technologies," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169820, Agricultural and Applied Economics Association.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7632-:d:414276. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.