IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v253y2021ics0378377421001967.html
   My bibliography  Save this article

Impact of grass traits on the transport path and retention efficiency of nitrate nitrogen in vegetation filter strips

Author

Listed:
  • Sheng, Liting
  • Zhang, Zhanyu
  • Xia, Jihong
  • Liang, Ziwei
  • Yang, Jie
  • Chen, Xiao-an

Abstract

Vegetation filter strips (VFS) have been shown to effectively intercept water flow and remove nitrogen. Studies of the vegetation effects on water flow and nitrogen transport are typically studied based on qualitative analyses with species, layouts, growth stage, seasonal changes, and other vegetation conditions and did not considered quantification based on plant traits. In this study, the transport path and retention efficiency of nitrate nitrogen (NO3-N) in VFSs are investigated from the view of the plant specific trait effects by simulating runoff experiments using three grassed VFSs (centipede grass, tall fescue, and vetiver grass), as well as a bare VFS under different slope gradients (2%, 7%, and 12% slope gradients). The primary grass traits (stem spacing, root depth, root length density, and nitrogen total uptake) were measured, and the responses of water flow and NO3-N loss above and below ground to those were quantitatively assessed using the grey correlation analysis method. Results indicated that grasses and slope gradient significantly influenced the water flow and NO3-N loss in general, except the NO3-N loss concentration of the surface flow, in which the tall fescue VFS showed the highest NO3-N total retention rates under each slope condition. Considering the impact of specific grass traits, stem density and root length density has the greatest effects on the surface flow and the subsurface flow respectively, while the effect of roots was lower than that of stems on NO3-N loss below ground. Additionally, the NO3-N loss mass in the surface and subsurface flow were mostly related to the water flow volume and the NO3-N loss concentration respectively. This indicated that grass traits that reduce water flow should be considered more to control the NO3-N loss mass above ground, whereas the grass traits reducing NO3-N loss concentration should be considered more to control the NO3-N loss mass below ground.

Suggested Citation

  • Sheng, Liting & Zhang, Zhanyu & Xia, Jihong & Liang, Ziwei & Yang, Jie & Chen, Xiao-an, 2021. "Impact of grass traits on the transport path and retention efficiency of nitrate nitrogen in vegetation filter strips," Agricultural Water Management, Elsevier, vol. 253(C).
    • Handle: RePEc:eee:agiwat:v:253:y:2021:i:c:s0378377421001967
    DOI: 10.1016/j.agwat.2021.106931
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377421001967
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2021.106931?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. Liting Sheng & Zhanyu Zhang & Jihong Xia & Jie Yang & Dan Tang & Xiao-an Chen, 2017. "The Impact of Vegetative Slope on Water Flow and Pollutant Transport through Embankments," Sustainability, MDPI, vol. 9(7), pages 1-12, June.
    2. Josep Peñuelas & Benjamin Poulter & Jordi Sardans & Philippe Ciais & Marijn van der Velde & Laurent Bopp & Olivier Boucher & Yves Godderis & Philippe Hinsinger & Joan Llusia & Elise Nardin & Sara Vicc, 2013. "Human-induced nitrogen–phosphorus imbalances alter natural and managed ecosystems across the globe," Nature Communications, Nature, vol. 4(1), pages 1-10, 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. Gbenga Abayomi Afuye & Ahmed Mukalazi Kalumba & Israel Ropo Orimoloye, 2021. "Characterisation of Vegetation Response to Climate Change: A Review," Sustainability, MDPI, vol. 13(13), pages 1-23, June.
    2. Asada, K. & Kanda, T. & Yamashita, N. & Asano, M. & Eguchi, S., 2022. "Interpreting stoichiometric homeostasis and flexibility of soil microbial biomass carbon, nitrogen, and phosphorus," Ecological Modelling, Elsevier, vol. 470(C).
    3. Li, Xiran & Zhu, Zaichun & Zeng, Hui & Piao, Shilong, 2016. "Estimation of gross primary production in China (1982–2010) with multiple ecosystem models," Ecological Modelling, Elsevier, vol. 324(C), pages 33-44.

    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:agiwat:v:253:y:2021:i:c:s0378377421001967. 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.elsevier.com/locate/agwat .

    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.