IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v10y2012i1p144-157d22455.html
   My bibliography  Save this article

Assessing the Influence of Land Use and Land Cover Datasets with Different Points in Time and Levels of Detail on Watershed Modeling in the North River Watershed, China

Author

Listed:
  • Jinliang Huang

    (Fujian Provincial Key Laboratory of Coastal Ecology and Environmental Studies, Xiamen University, Xiamen 361005, China
    College of the Environment and Ecology, Xiamen University, Xiamen 361005, China)

  • Pei Zhou

    (College of the Environment and Ecology, Xiamen University, Xiamen 361005, China)

  • Zengrong Zhou

    (Department of Environmental Science and Engineering, Huaqiao University, Xiamen 361021, China)

  • Yaling Huang

    (College of the Environment and Ecology, Xiamen University, Xiamen 361005, China)

Abstract

Land use and land cover (LULC) information is an important component influencing watershed modeling with regards to hydrology and water quality in the river basin. In this study, the sensitivity of the Soil and Water Assessment Tool (SWAT) model to LULC datasets with three points in time and three levels of detail was assessed in a coastal subtropical watershed located in Southeast China. The results showed good agreement between observed and simulated values for both monthly and daily streamflow and monthly NH 4 + -N and TP loads. Three LULC datasets in 2002, 2007 and 2010 had relatively little influence on simulated monthly and daily streamflow, whereas they exhibited greater effects on simulated monthly NH 4 + -N and TP loads. When using the two LULC datasets in 2007 and 2010 compared with that in 2002, the relative differences in predicted monthly NH 4 + -N and TP loads were −11.0 to −7.8% and −4.8 to −9.0%, respectively. There were no significant differences in simulated monthly and daily streamflow when using the three LULC datasets with ten, five and three categories. When using LULC datasets from ten categories compared to five and three categories, the relative differences in predicted monthly NH 4 + -N and TP loads were −6.6 to −6.5% and −13.3 to −7.3%, respectively. Overall, the sensitivity of the SWAT model to LULC datasets with different points in time and levels of detail was lower in monthly and daily streamflow simulation than in monthly NH 4 + -N and TP loads prediction. This research provided helpful insights into the influence of LULC datasets on watershed modeling.

Suggested Citation

  • Jinliang Huang & Pei Zhou & Zengrong Zhou & Yaling Huang, 2012. "Assessing the Influence of Land Use and Land Cover Datasets with Different Points in Time and Levels of Detail on Watershed Modeling in the North River Watershed, China," IJERPH, MDPI, vol. 10(1), pages 1-14, December.
    • Handle: RePEc:gam:jijerp:v:10:y:2012:i:1:p:144-157:d:22455
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/10/1/144/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/10/1/144/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Li-Chi Chiang & Indrajeet Chaubey & Chetan Maringanti & Tao Huang, 2014. "Comparing the Selection and Placement of Best Management Practices in Improving Water Quality Using a Multiobjective Optimization and Targeting Method," IJERPH, MDPI, vol. 11(3), pages 1-23, March.

    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:jijerp:v:10:y:2012:i:1:p:144-157:d:22455. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.