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Modelling triazines in the valley of the River Cauca, Colombia, using the annualized agricultural non-point source pollution model

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  • Villamizar, Martha L.
  • Brown, Colin D.

Abstract

The annualized agricultural non-point source pollution model (AnnAGNPS) was applied to simulate losses of triazine herbicides to the River Cauca following application to sugarcane, maize and sorghum in the Cauca Valley of Colombia. Surface runoff was found to be the main driver of triazine losses to surface water in the catchment. Satisfactory simulation and validation of the hydrology was achieved after little calibration (Nash-Sutcliffe model efficiency=0.70 and r2=0.73). A fairly good simulation of pesticides was generally achieved, but some patterns in the measured data could not be simulated. Uncertainty analyses of sensitive input parameters were carried out which explained most of the concentrations that were not captured by the initial simulation; however, evidence of point source pollution was observed for some large concentrations measured upstream. Replacing triazine herbicides with mesotrione was predicted to result in an 87% reduction in pesticide losses expressed as a proportion of the total pesticide applied.

Suggested Citation

  • Villamizar, Martha L. & Brown, Colin D., 2016. "Modelling triazines in the valley of the River Cauca, Colombia, using the annualized agricultural non-point source pollution model," Agricultural Water Management, Elsevier, vol. 177(C), pages 24-36.
    • Handle: RePEc:eee:agiwat:v:177:y:2016:i:c:p:24-36
    DOI: 10.1016/j.agwat.2016.06.010
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    References listed on IDEAS

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    1. Chahor, Y. & Casalí, J. & Giménez, R. & Bingner, R.L. & Campo, M.A. & Goñi, M., 2014. "Evaluation of the AnnAGNPS model for predicting runoff and sediment yield in a small Mediterranean agricultural watershed in Navarre (Spain)," Agricultural Water Management, Elsevier, vol. 134(C), pages 24-37.
    2. Leon, L. F. & Booty, W. G. & Bowen, G. S. & Lam, D. C. L., 2004. "Validation of an agricultural non-point source model in a watershed in southern Ontario," Agricultural Water Management, Elsevier, vol. 65(1), pages 59-75, February.
    3. Holvoet, Katrijn M.A. & Seuntjens, Piet & Vanrolleghem, Peter A., 2007. "Monitoring and modeling pesticide fate in surface waters at the catchment scale," Ecological Modelling, Elsevier, vol. 209(1), pages 53-64.
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    Cited by:

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    2. Ying Chen & Binbin Lu & Chongyu Xu & Xingwei Chen & Meibing Liu & Lu Gao & Haijun Deng, 2022. "Uncertainty Evaluation of Best Management Practice Effectiveness Based on the AnnAGNPS Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1307-1321, March.
    3. Zhao, Danyue & Liu, Wenxin & Gao, Rong & Zhang, Ping & Li, Meng & Wu, Pute & Zhuo, La, 2023. "Spatiotemporal evolution of crop grey water footprint and associated water pollution levels in arid regions of western China," Agricultural Water Management, Elsevier, vol. 280(C).
    4. Wan, Wei & Han, Yiwen & Wu, Hanqing & Liu, Fan & Liu, Zhong, 2021. "Application of the source–sink landscape method in the evaluation of agricultural non-point source pollution: First estimation of an orchard-dominated area in China," Agricultural Water Management, Elsevier, vol. 252(C).

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