IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v470y2022ics0304380022001302.html
   My bibliography  Save this article

Simulation of N2O emissions from greenhouse vegetable production under different management systems in North China

Author

Listed:
  • Zhang, Hongyuan
  • Batchelor, William D.
  • Hu, Kelin
  • Liang, Hao
  • Han, Hui
  • Li, Ji

Abstract

Quantifying greenhouse gas emissions from greenhouse vegetable production systems (GVPS) is helpful to direct carbon sequestration and greenhouse gas emissions reduction. The objectives of this study were to (i) evaluate the performance of the improved WHCNS-Veg model (soil Water Heat Carbon Nitrogen Simulation for Vegetable) in simulating nitrous oxide (N2O) emissions under different GVPS and (ii) analyze the impact of different management systems on N2O emissions from the GVPS. Greenhouse vegetable experiments were carried out under different management systems, including conventional (CON), integrated (INT) and organic (ORG), in Quzhou County, Hebei province from 2013 to 2015. Field observations of soil water content, soil nitrate concentration and N2O emissions were used to calibrate and validate the WHCNS-Veg model. The sensitivity analysis results showed that the effects of soil hydraulic parameters on N2O emissions were higher than those of N transformation and vegetable genetic parameters. The improved WHCNS-Veg model simulated soil water content, soil nitrate concentration and N2O emissions well under different GVPS. The average N2O emissions in the spring-summer season (16.3 kg N ha−1) were about 2.5 times higher than the autumn-winter season (6.4 kg N ha−1). Among the four seasons, the average N2O emissions of CON, ORG and INT were 13.5, 11.3 and 9.3 kg N ha−1, respectively, accounting for 1.4–1.7% of the total fertilizer input. The N2O emissions of the INT and ORG systems were 31.1% and 16.3% lower than the CON treatment, respectively. The results indicated that the improved WHCNS-Veg model can be used to simulate and analyze N2O emissions under different management systems and substituting organic manure for chemical fertilizer could effectively reduce the N2O emissions in the GVPS.

Suggested Citation

  • Zhang, Hongyuan & Batchelor, William D. & Hu, Kelin & Liang, Hao & Han, Hui & Li, Ji, 2022. "Simulation of N2O emissions from greenhouse vegetable production under different management systems in North China," Ecological Modelling, Elsevier, vol. 470(C).
    • Handle: RePEc:eee:ecomod:v:470:y:2022:i:c:s0304380022001302
    DOI: 10.1016/j.ecolmodel.2022.110019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380022001302
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2022.110019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Šimůnek, Jiří & Hopmans, Jan W., 2009. "Modeling compensated root water and nutrient uptake," Ecological Modelling, Elsevier, vol. 220(4), pages 505-521.
    2. Liang, Hao & Lv, Haofeng & Batchelor, William D. & Lian, Xiaojuan & Wang, Zhengxiang & Lin, Shan & Hu, Kelin, 2020. "Simulating nitrate and DON leaching to optimize water and N management practices for greenhouse vegetable production systems," Agricultural Water Management, Elsevier, vol. 241(C).
    3. Liang, Hao & Hu, Kelin & Batchelor, William D. & Qin, Wei & Li, Baoguo, 2018. "Developing a water and nitrogen management model for greenhouse vegetable production in China: Sensitivity analysis and evaluation," Ecological Modelling, Elsevier, vol. 367(C), pages 24-33.
    4. Li, Yong & White, Robert & Chen, Deli & Zhang, Jiabao & Li, Baoguo & Zhang, Yuming & Huang, Yuanfang & Edis, Robert, 2007. "A spatially referenced water and nitrogen management model (WNMM) for (irrigated) intensive cropping systems in the North China Plain," Ecological Modelling, Elsevier, vol. 203(3), pages 395-423.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liang, Hao & Xu, Junzeng & Hou, Huijing & Qi, Zhiming & Yang, Shihong & Li, Yawei & Hu, Kelin, 2022. "Modeling CH4 and N2O emissions for continuous and noncontinuous flooding rice systems," Agricultural Systems, Elsevier, vol. 203(C).

    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. Wang, Xiangping & Huang, Guanhua & Yang, Jingsong & Huang, Quanzhong & Liu, Haijun & Yu, Lipeng, 2015. "An assessment of irrigation practices: Sprinkler irrigation of winter wheat in the North China Plain," Agricultural Water Management, Elsevier, vol. 159(C), pages 197-208.
    2. Wang, Xiangping & Liu, Guangming & Yang, Jingsong & Huang, Guanhua & Yao, Rongjiang, 2017. "Evaluating the effects of irrigation water salinity on water movement, crop yield and water use efficiency by means of a coupled hydrologic/crop growth model," Agricultural Water Management, Elsevier, vol. 185(C), pages 13-26.
    3. Liang, Hao & Hu, Kelin & Batchelor, William D. & Qin, Wei & Li, Baoguo, 2018. "Developing a water and nitrogen management model for greenhouse vegetable production in China: Sensitivity analysis and evaluation," Ecological Modelling, Elsevier, vol. 367(C), pages 24-33.
    4. Chen, Shichao & Parsons, David & Du, Taisheng & Kumar, Uttam & Wang, Sufen, 2021. "Simulation of yield and water balance using WHCNS and APSIM combined with geostatistics across a heterogeneous field," Agricultural Water Management, Elsevier, vol. 258(C).
    5. Phogat, V. & Skewes, M.A. & Cox, J.W. & Alam, J. & Grigson, G. & Šimůnek, J., 2013. "Evaluation of water movement and nitrate dynamics in a lysimeter planted with an orange tree," Agricultural Water Management, Elsevier, vol. 127(C), pages 74-84.
    6. Wang, Jianjun & Wang, Chuantao & Li, Hongchen & Liu, Yanfang & Li, Huijie & Ren, Ruiqi & Si, Bingcheng, 2023. "Rock water use by apple trees affected by physical properties of the underlying weathered rock," Agricultural Water Management, Elsevier, vol. 287(C).
    7. Rosa, R.D. & Ramos, T.B. & Pereira, L.S., 2016. "The dual Kc approach to assess maize and sweet sorghum transpiration and soil evaporation under saline conditions: Application of the SIMDualKc model," Agricultural Water Management, Elsevier, vol. 177(C), pages 77-94.
    8. Mubarak, Ibrahim & Mailhol, Jean Claude & Angulo-Jaramillo, Rafael & Bouarfa, Sami & Ruelle, Pierre, 2009. "Effect of temporal variability in soil hydraulic properties on simulated water transfer under high-frequency drip irrigation," Agricultural Water Management, Elsevier, vol. 96(11), pages 1547-1559, November.
    9. Sonkar, Ickkshaanshu & Kotnoor, Hari Prasad & Sen, Sumit, 2019. "Estimation of root water uptake and soil hydraulic parameters from root zone soil moisture and deep percolation," Agricultural Water Management, Elsevier, vol. 222(C), pages 38-47.
    10. Margarita A. Petoussi & Nicolas Kalogerakis, 2023. "Mathematical Modeling of Pilot Scale Olive Mill Wastewater Phytoremediation Units," Sustainability, MDPI, vol. 15(11), pages 1-36, May.
    11. Müller, T. & Ranquet Bouleau, C. & Perona, P., 2016. "Optimizing drip irrigation for eggplant crops in semi-arid zones using evolving thresholds," Agricultural Water Management, Elsevier, vol. 177(C), pages 54-65.
    12. Fabio V. Difonzo & Costantino Masciopinto & Michele Vurro & Marco Berardi, 2021. "Shooting the Numerical Solution of Moisture Flow Equation with Root Water Uptake Models: A Python Tool," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2553-2567, June.
    13. Bughici, Theodor & Skaggs, Todd H. & Corwin, Dennis L. & Scudiero, Elia, 2022. "Ensemble HYDRUS-2D modeling to improve apparent electrical conductivity sensing of soil salinity under drip irrigation," Agricultural Water Management, Elsevier, vol. 272(C).
    14. Wulder, Michael A. & White, Joanne C. & Coops, Nicholas C. & Nelson, Trisalyn & Boots, Barry, 2007. "Using local spatial autocorrelation to compare outputs from a forest growth model," Ecological Modelling, Elsevier, vol. 209(2), pages 264-276.
    15. Li, Huijie & Ma, Xiaojun & Lu, Yanwei & Ren, Ruiqi & Cui, Buli & Si, Bingcheng, 2021. "Growing deep roots has opposing impacts on the transpiration of apple trees planted in subhumid loess region," Agricultural Water Management, Elsevier, vol. 258(C).
    16. Minhas, P.S. & Ramos, Tiago B. & Ben-Gal, Alon & Pereira, Luis S., 2020. "Coping with salinity in irrigated agriculture: Crop evapotranspiration and water management issues," Agricultural Water Management, Elsevier, vol. 227(C).
    17. Che, Zheng & Wang, Jun & Li, Jiusheng, 2022. "Modeling strategies to balance salt leaching and nitrogen loss for drip irrigation with saline water in arid regions," Agricultural Water Management, Elsevier, vol. 274(C).
    18. Naghedifar, Seyed Mohammadreza & Ziaei, Ali Naghi, 2023. "EBMAN-HP: A parallel model for simulation of sensor-based ebb-and-flow subirrigation systems," Agricultural Water Management, Elsevier, vol. 275(C).
    19. Tan, Xuezhi & Shao, Dongguo & Gu, Wenquan & Liu, Huanhuan, 2015. "Field analysis of water and nitrogen fate in lowland paddy fields under different water managements using HYDRUS-1D," Agricultural Water Management, Elsevier, vol. 150(C), pages 67-80.
    20. Azad, Nasrin & Behmanesh, Javad & Rezaverdinejad, Vahid & Abbasi, Fariborz & Navabian, Maryam, 2018. "Developing an optimization model in drip fertigation management to consider environmental issues and supply plant requirements," Agricultural Water Management, Elsevier, vol. 208(C), pages 344-356.

    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:eee:ecomod:v:470:y:2022:i:c:s0304380022001302. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    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.