IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i24p16381-d996618.html
   My bibliography  Save this article

Influence of Different Meteorological Factors on the Accuracy of Back Propagation Neural Network Simulation of Soil Moisture in China

Author

Listed:
  • Yuyan Liu

    (School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China
    Aerospace Remote Sensing Information Processing and Application Collaborative Innovation Center of Hebei Province, Langfang 065000, China
    National Joint Engineering Research Center of Space Remote Sensing Information Application Technology, Langfang 065000, China)

  • Fei Shi

    (School of Liberal Arts and Sciences, North China Institute of Aerospace Engineering, Langfang 065000, China)

  • Xuan Liu

    (School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China
    Aerospace Remote Sensing Information Processing and Application Collaborative Innovation Center of Hebei Province, Langfang 065000, China
    National Joint Engineering Research Center of Space Remote Sensing Information Application Technology, Langfang 065000, China)

  • Zihui Zhao

    (School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China
    Aerospace Remote Sensing Information Processing and Application Collaborative Innovation Center of Hebei Province, Langfang 065000, China
    National Joint Engineering Research Center of Space Remote Sensing Information Application Technology, Langfang 065000, China)

  • Yongtao Jin

    (School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China
    Aerospace Remote Sensing Information Processing and Application Collaborative Innovation Center of Hebei Province, Langfang 065000, China
    National Joint Engineering Research Center of Space Remote Sensing Information Application Technology, Langfang 065000, China)

  • Yulin Zhan

    (Space Information Innovation Institute, Chinese Academy of Sciences, Beijing 100190, China)

  • Xia Zhu

    (School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China
    Aerospace Remote Sensing Information Processing and Application Collaborative Innovation Center of Hebei Province, Langfang 065000, China
    National Joint Engineering Research Center of Space Remote Sensing Information Application Technology, Langfang 065000, China)

  • Wei Luo

    (School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China
    Aerospace Remote Sensing Information Processing and Application Collaborative Innovation Center of Hebei Province, Langfang 065000, China
    National Joint Engineering Research Center of Space Remote Sensing Information Application Technology, Langfang 065000, China)

  • Wenhao Zhang

    (School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China
    Aerospace Remote Sensing Information Processing and Application Collaborative Innovation Center of Hebei Province, Langfang 065000, China
    National Joint Engineering Research Center of Space Remote Sensing Information Application Technology, Langfang 065000, China)

  • Yuefang Sun

    (School of Liberal Arts and Sciences, North China Institute of Aerospace Engineering, Langfang 065000, China)

  • Xuqing Li

    (School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China
    Aerospace Remote Sensing Information Processing and Application Collaborative Innovation Center of Hebei Province, Langfang 065000, China
    National Joint Engineering Research Center of Space Remote Sensing Information Application Technology, Langfang 065000, China)

  • Yancang Wang

    (School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China
    Aerospace Remote Sensing Information Processing and Application Collaborative Innovation Center of Hebei Province, Langfang 065000, China
    National Joint Engineering Research Center of Space Remote Sensing Information Application Technology, Langfang 065000, China)

Abstract

Soil moisture is one of the most critical elements of the Earth system and is essential for the study of the terrestrial water cycle, ecological processes, climate change, and disaster warnings. In this study, the training sample was selected to divide the dataset according to months from 2000 to 2018 after the advantages of three training samples were compared using a backpropagation (BP) neural network model. Furthermore, the monthly surface soil moisture in China in 2019 and 2020 was simulated based on various meteorological elements. The results demonstrate that evapotranspiration has the greatest influence on soil moisture among the various meteorological factors, followed by precipitation on a national scale throughout the year. Additionally, the accuracy of the training and simulation results with BP neural networks in the national winter months is slightly worse. In the future, the training samples of the BP neural network can be optimized following the differences in the dominant influence of various meteorological factors on soil moisture in different areas at different times to improve the simulation prediction accuracy.

Suggested Citation

  • Yuyan Liu & Fei Shi & Xuan Liu & Zihui Zhao & Yongtao Jin & Yulin Zhan & Xia Zhu & Wei Luo & Wenhao Zhang & Yuefang Sun & Xuqing Li & Yancang Wang, 2022. "Influence of Different Meteorological Factors on the Accuracy of Back Propagation Neural Network Simulation of Soil Moisture in China," Sustainability, MDPI, vol. 14(24), pages 1-23, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16381-:d:996618
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/24/16381/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/24/16381/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Holsten, Anne & Vetter, Tobias & Vohland, Katrin & Krysanova, Valentina, 2009. "Impact of climate change on soil moisture dynamics in Brandenburg with a focus on nature conservation areas," Ecological Modelling, Elsevier, vol. 220(17), pages 2076-2087.
    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. Hlavinka, Petr & Trnka, Miroslav & Balek, Jan & Semerádová, Daniela & Hayes, Michael & Svoboda, Mark & Eitzinger, Josef & Mozný, Martin & Fischer, Milan & Hunt, Eric & Zalud, Zdenek, 2011. "Development and evaluation of the SoilClim model for water balance and soil climate estimates," Agricultural Water Management, Elsevier, vol. 98(8), pages 1249-1261, May.
    2. Fouad H. Saeed & Mahmoud S. Al-Khafaji & Furat A. Mahmood Al-Faraj, 2021. "Sensitivity of Irrigation Water Requirement to Climate Change in Arid and Semi-Arid Regions towards Sustainable Management of Water Resources," Sustainability, MDPI, vol. 13(24), pages 1-21, December.
    3. Sumaiya Jarin Ahammed & Rajab Homsi & Najeebullah Khan & Shamsuddin Shahid & Mohammed Sanusi Shiru & Morteza Mohsenipour & Kamal Ahmed & Nadeem Nawaz & Nor Eliza Alias & Ali Yuzir, 2020. "Assessment of changing pattern of crop water stress in Bangladesh," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(5), pages 4619-4637, June.
    4. MB Dastagiri & Anjani Sneha Vajrala, 2018. "Financing Climate Change on Global Agriculture-An Overview," International Journal of Environmental Sciences & Natural Resources, Juniper Publishers Inc., vol. 12(5), pages 148-153, July.
    5. Amfo, Bismark & Ali, Ernest Baba & Atinga, David, 2021. "Climate change, soil water conservation, and productivity: Evidence from cocoa farmers in Ghana," Agricultural Systems, Elsevier, vol. 191(C).
    6. Agathos Filintas & Nikolaos Gougoulias & Nektarios Kourgialas & Eleni Hatzichristou, 2023. "Management Soil Zones, Irrigation, and Fertigation Effects on Yield and Oil Content of Coriandrum sativum L. Using Precision Agriculture with Fuzzy k-Means Clustering," Sustainability, MDPI, vol. 15(18), pages 1-33, September.

    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:14:y:2022:i:24:p:16381-:d:996618. 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.