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Response of Non-point Source Pollution Loads to Land Use Change under Different Precipitation Scenarios from a Future Perspective

Author

Listed:
  • Xiaoyan Bai

    (Guangdong University of Technology)

  • Wen Shen

    (Guangdong University of Technology)

  • Peng Wang

    (Guangdong University of Technology
    Jinan University)

  • Xiaohong Chen

    (Sun Yat-sen University)

  • Yanhu He

    (Guangdong University of Technology)

Abstract

To optimize the management of non-point source (NPS) pollution in a changing environment, the cellular automata (CA) and Hydrological Simulation Program-Fortran (HSPF) models were used to study the response mechanism of NPS pollution loads to land use change and different precipitation scenarios. Taking the Dongjiang River Basin as a case study, the land use situation and its spatial distribution patterns in 2020, 2030 and 2050 were predicted by the logistic regression-based CA model. The trends of the NPS pollution loads under different land use and precipitation scenarios were quantitatively evaluated. The results show that the total accuracy of the land use change simulated by the CA model was 81%. Both the HSPF model and the CA model were highly applicable to this basin. Precipitation is proven to be the main driving force of NPS pollution. From 2020 to 2050, the annual load, average monthly load, maximum and minimum monthly load of the BOD and TP show an upward trend. TN shows a slight downward trend, which is related to the reduction in cultivated land area and the use of nitrogen fertilizer. In view of the future trend of NPS pollution, the basin should continue to control TN pollution and focus on strengthening BOD and TP control to achieve high-quality management of the water environment.

Suggested Citation

  • Xiaoyan Bai & Wen Shen & Peng Wang & Xiaohong Chen & Yanhu He, 2020. "Response of Non-point Source Pollution Loads to Land Use Change under Different Precipitation Scenarios from a Future Perspective," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(13), pages 3987-4002, October.
    • Handle: RePEc:spr:waterr:v:34:y:2020:i:13:d:10.1007_s11269-020-02626-0
    DOI: 10.1007/s11269-020-02626-0
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    References listed on IDEAS

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    1. Jinyao Lin & Tongli Chen & Qiazi Han, 2018. "Simulating and Predicting the Impacts of Light Rail Transit Systems on Urban Land Use by Using Cellular Automata: A Case Study of Dongguan, China," Sustainability, MDPI, vol. 10(4), pages 1-16, April.
    2. Ribarova, Irina & Ninov, Plamen & Cooper, David, 2008. "Modeling nutrient pollution during a first flood event using HSPF software: Iskar River case study, Bulgaria," Ecological Modelling, Elsevier, vol. 211(1), pages 241-246.
    3. S. K. Aryal & S. Ashbolt & B. S. McIntosh & K. P. Petrone & S. Maheepala & R. K. Chowdhury & T. Gardener & R. Gardiner, 2016. "Assessing and Mitigating the Hydrological Impacts of Urbanisation in Semi-Urban Catchments Using the Storm Water Management Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5437-5454, November.
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    Cited by:

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    3. 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.
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    5. Xiao Zhang & Xiaomin Chen & Wanshun Zhang & Hong Peng & Gaohong Xu & Yanxin Zhao & Zhenling Shen, 2022. "Impact of Land Use Changes on the Surface Runoff and Nutrient Load in the Three Gorges Reservoir Area, China," Sustainability, MDPI, vol. 14(4), pages 1-21, February.

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