IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i7p2942-d1368662.html
   My bibliography  Save this article

Estimation of Corn Net Primary Productivity and Carbon Sequestration Based on the CASA Model: A Case Study of the Fen River Basin

Author

Listed:
  • Zhiqiang Zhang

    (School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Lijuan Huo

    (School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Yuxin Su

    (School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • He Shen

    (School of Geography and Tourism, Shaanxi Normal University, Xi’an 710062, China)

  • Gaiqiang Yang

    (School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China
    Agricultural Hydropower Department, Department of Water Resources of Shanxi Province, Taiyuan 030002, China)

Abstract

The utilization of remote sensing technology to assess changes in crop net primary productivity (NPP), biomass, and carbon sequestration within the Fen River Basin, a crucial agricultural region in China, is important for achieving agricultural modernization, enhancing ecological environment quality, and obtaining carbon neutrality objectives. This study employed satellite remote sensing and the Carnegie–Ames–Stanford approach (CASA) model as research methods to investigate the temporal and spatial distribution characteristics of corn NPP in the Fen River Basin. Correlation analysis was conducted to examine the response of corn NPP to various environmental factors in the region, while aboveground biomass and carbon sequestration of corn were estimated using a biomass inversion model driven by NPP and principles of photosynthesis in green plants. The findings revealed that, from a temporal perspective, corn NPP in the Fen River Basin exhibited a unimodal variation pattern, with an average value of 368.65 gC/m 2 . Spatially, the corn NPP displayed a discernible differentiation pattern, with the highest values primarily observed in the middle reaches of the Fen River Basin. Throughout the spatial and temporal variations in corn NPP during 2011–2020, the carbon sequestration capacity of corn exhibited an upward trend, particularly since 2017. The corn NPP displayed a positive correlation with temperature and precipitation. The response to solar radiation was mildly negative and a mildly positive correlation. In 2020, the aboveground biomass and carbon sequestration of corn followed a normal distribution, with the highest values concentrated in the northwestern part of the lower Fen River.

Suggested Citation

  • Zhiqiang Zhang & Lijuan Huo & Yuxin Su & He Shen & Gaiqiang Yang, 2024. "Estimation of Corn Net Primary Productivity and Carbon Sequestration Based on the CASA Model: A Case Study of the Fen River Basin," Sustainability, MDPI, vol. 16(7), pages 1-18, April.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:7:p:2942-:d:1368662
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/7/2942/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/7/2942/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6809), pages 184-187, November.
    2. Robinson, D.T. & Brown, D.G. & Currie, W.S., 2009. "Modelling carbon storage in highly fragmented and human-dominated landscapes: Linking land-cover patterns and ecosystem models," Ecological Modelling, Elsevier, vol. 220(9), pages 1325-1338.
    3. Wan, Wei & Liu, Zhong & Li, Kejiang & Wang, Guiman & Wu, Hanqing & Wang, Qingyun, 2021. "Drought monitoring of the maize planting areas in Northeast and North China Plain," Agricultural Water Management, Elsevier, vol. 245(C).
    4. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Erratum: Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6813), pages 750-750, December.
    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. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2018. "And then he wasn't a she : Climate change and green transitions in an agent-based integrated assessment model," Working Papers hal-03443464, HAL.
    2. Govind, Ajit & Chen, Jing Ming & Bernier, Pierre & Margolis, Hank & Guindon, Luc & Beaudoin, Andre, 2011. "Spatially distributed modeling of the long-term carbon balance of a boreal landscape," Ecological Modelling, Elsevier, vol. 222(15), pages 2780-2795.
    3. Eliseev, Alexey V. & Mokhov, Igor I., 2008. "Eventual saturation of the climate–carbon cycle feedback studied with a conceptual model," Ecological Modelling, Elsevier, vol. 213(1), pages 127-132.
    4. Brovkin, Victor & Cherkinsky, Alexander & Goryachkin, Sergey, 2008. "Estimating soil carbon turnover using radiocarbon data: A case-study for European Russia," Ecological Modelling, Elsevier, vol. 216(2), pages 178-187.
    5. Ulaganathan, Kandasamy & Goud, Sravanthi & Reddy, Madhavi & Kayalvili, Ulaganathan, 2017. "Genome engineering for breaking barriers in lignocellulosic bioethanol production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1080-1107.
    6. Brazhnik, Ksenia & Shugart, H.H., 2016. "SIBBORK: A new spatially-explicit gap model for boreal forest," Ecological Modelling, Elsevier, vol. 320(C), pages 182-196.
    7. Kai Yin & Dengsheng Lu & Yichen Tian & Qianjun Zhao & Chao Yuan, 2014. "Evaluation of Carbon and Oxygen Balances in Urban Ecosystems Using Land Use/Land Cover and Statistical Data," Sustainability, MDPI, vol. 7(1), pages 1-27, December.
    8. Agudelo, César Augusto Ruiz & Bustos, Sandra Liliana Hurtado & Moreno, Carmen Alicia Parrado, 2020. "Modeling interactions among multiple ecosystem services. A critical review," Ecological Modelling, Elsevier, vol. 429(C).
    9. Ouardighi, Fouad El & Sim, Jeong Eun & Kim, Bowon, 2016. "Pollution accumulation and abatement policy in a supply chain," European Journal of Operational Research, Elsevier, vol. 248(3), pages 982-996.
    10. Kim, Hyeyoung & House, Lisa A. & KIm, Tae-Kyun, 2016. "Consumer perceptions of climate change and willingness to pay for mandatory implementation of low carbon labels: the case of South Korea," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(4), October.
    11. Guoju, Xiao & Weixiang, Liu & Qiang, Xu & Zhaojun, Sun & Jing, Wang, 2005. "Effects of temperature increase and elevated CO2 concentration, with supplemental irrigation, on the yield of rain-fed spring wheat in a semiarid region of China," Agricultural Water Management, Elsevier, vol. 74(3), pages 243-255, June.
    12. Sogol Moradian & Farhad Yazdandoost, 2021. "Seasonal meteorological drought projections over Iran using the NMME data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 1089-1107, August.
    13. Viola, Flavio M. & Paiva, Susana L.D. & Savi, Marcelo A., 2010. "Analysis of the global warming dynamics from temperature time series," Ecological Modelling, Elsevier, vol. 221(16), pages 1964-1978.
    14. Farrelly, Damien J. & Everard, Colm D. & Fagan, Colette C. & McDonnell, Kevin P., 2013. "Carbon sequestration and the role of biological carbon mitigation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 712-727.
    15. Marc Kennedy & Clive Anderson & Anthony O'Hagan & Mark Lomas & Ian Woodward & John Paul Gosling & Andreas Heinemeyer, 2008. "Quantifying uncertainty in the biospheric carbon flux for England and Wales," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 109-135, January.
    16. Yonghua Li & Song Yao & Hezhou Jiang & Huarong Wang & Qinchuan Ran & Xinyun Gao & Xinyi Ding & Dandong Ge, 2022. "Spatial-Temporal Evolution and Prediction of Carbon Storage: An Integrated Framework Based on the MOP–PLUS–InVEST Model and an Applied Case Study in Hangzhou, East China," Land, MDPI, vol. 11(12), pages 1-22, December.
    17. Sara J. Germain & James A. Lutz, 2020. "Climate extremes may be more important than climate means when predicting species range shifts," Climatic Change, Springer, vol. 163(1), pages 579-598, November.
    18. Xiongwen Chen & Wilfred Post & Richard Norby & Aimée Classen, 2011. "Modeling soil respiration and variations in source components using a multi-factor global climate change experiment," Climatic Change, Springer, vol. 107(3), pages 459-480, August.
    19. Wang, Tao & Yu, Wei & Le Moullec, Yann & Liu, Fei & Xiong, Yili & He, Hui & Lu, Jiahui & Hsu, Emily & Fang, Mengxiang & Luo, Zhongyang, 2017. "Solvent regeneration by novel direct non-aqueous gas stripping process for post-combustion CO2 capture," Applied Energy, Elsevier, vol. 205(C), pages 23-32.
    20. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2018. "Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model," Ecological Economics, Elsevier, vol. 150(C), pages 315-339.

    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:16:y:2024:i:7:p:2942-:d:1368662. 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.