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A comprehensive study of the effect of GIS data on hydrology and non-point source pollution modeling

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  • Shen, Z.Y.
  • Chen, L.
  • Liao, Q.
  • Liu, R.M.
  • Huang, Q.

Abstract

The Geographic Information System (GIS) has been extensively integrated into hydrology and non-point source (H/NPS) pollution modeling. However, few studies have been carried out on the effect of GIS inputs on NPS modeling and the prediction uncertainty related to the combination of different GIS inputs. In this paper, the effect of GIS data on H/NPS simulation was investigated by re-sampling the initial GIS data into new grid sizes and grouping the available GIS maps in all possible ways. The effect of GIS inputs was then quantified by the Soil and Water Assessment Tool (SWAT) in the Daning watershed, China. Based on the results, the GIS inputs had a limited impact on runoff and nitrogen (N) predictions, while sediment and phosphorus (P) simulations were sensitively biased by GIS data. This study further demonstrated that a level (threshold) of GIS resolution existed, within which more precise data would not be of benefit to SWAT prediction. To reduce prediction uncertainty, the digital elevation model (DEM) should be tackled to determine at which resolution the model would perform optimally.

Suggested Citation

  • Shen, Z.Y. & Chen, L. & Liao, Q. & Liu, R.M. & Huang, Q., 2013. "A comprehensive study of the effect of GIS data on hydrology and non-point source pollution modeling," Agricultural Water Management, Elsevier, vol. 118(C), pages 93-102.
    • Handle: RePEc:eee:agiwat:v:118:y:2013:i:c:p:93-102
    DOI: 10.1016/j.agwat.2012.12.005
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    References listed on IDEAS

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    1. Tan, Q. & Huang, G.H. & Cai, Y.P., 2011. "Radial interval chance-constrained programming for agricultural non-point source water pollution control under uncertainty," Agricultural Water Management, Elsevier, vol. 98(10), pages 1595-1606, August.
    2. Fernandez, G.P. & Chescheir, G.M. & Skaggs, R.W. & Amatya, D.M., 2006. "DRAINMOD-GIS: A lumped parameter watershed scale drainage and water quality model," Agricultural Water Management, Elsevier, vol. 81(1-2), pages 77-97, March.
    3. Gassman, Philip W. & Reyes, Manuel R. & Green, Colleen H. & Arnold, Jeffrey G., 2007. "The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions," ISU General Staff Papers 200701010800001027, Iowa State University, Department of Economics.
    4. Li, W. & Li, Y.P. & Li, C.H. & Huang, G.H., 2010. "An inexact two-stage water management model for planning agricultural irrigation under uncertainty," Agricultural Water Management, Elsevier, vol. 97(11), pages 1905-1914, November.
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    Cited by:

    1. Shi, Yingyuan & Xu, Gaohong & Wang, Yonggui & Engel, Bernard A. & Peng, Hong & Zhang, Wanshun & Cheng, Meiling & Dai, Minglong, 2017. "Modelling hydrology and water quality processes in the Pengxi River basin of the Three Gorges Reservoir using the soil and water assessment tool," Agricultural Water Management, Elsevier, vol. 182(C), pages 24-38.
    2. Shan, Nan & Ruan, Xiao-Hong & Xu, Jing & Pan, Zha-Rong, 2014. "Estimating the optimal width of buffer strip for nonpoint source pollution control in the Three Gorges Reservoir Area, China," Ecological Modelling, Elsevier, vol. 276(C), pages 51-63.

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