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Demonstrating the Underestimated Effect of Landscape Pattern on Total Nitrogen and Total Phosphorus Concentrations Based on Cellular Automata–Markov Model in Taihu Lake Basin

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  • Yanan Wang

    (College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
    Key Laboratory of Hydrologic-Cycle and Hydrodynamic-System of Ministry of Water Resources, Hohai University, Nanjing 210098, China
    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China)

  • Guishan Yang

    (Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
    College of Geography and Remote Sensing, Hohai University, Nanjing 210098, China)

  • Saiyu Yuan

    (College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
    Key Laboratory of Hydrologic-Cycle and Hydrodynamic-System of Ministry of Water Resources, Hohai University, Nanjing 210098, China)

  • Jiacong Huang

    (Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China)

  • Hongwu Tang

    (College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
    Key Laboratory of Hydrologic-Cycle and Hydrodynamic-System of Ministry of Water Resources, Hohai University, Nanjing 210098, China)

Abstract

The expanding cropland profoundly affects stream water quality. However, the relationships between landscape patterns and stream water quality in different cropland composition classes remain unclear. We observed total nitrogen (TN), total phosphorus (TP) concentrations, and landscape patterns changed in 78 sub-watersheds of the Taihu Lake Basin’s Jiangsu segment from 2005 to 2020. The results showed that cropland area was positively correlated with TN and TP concentrations. The 21.10% reduction in cropland area, coupled with a 41.00% increase in building land, has led to an escalation in cropland fragmentation. Meanwhile, TN and TP concentrations declined by 26.67% and 28.57%, respectively. Partial least squares suggested that forest interspersion and juxtaposition metrics and forest area percentage were dominant factors influencing water quality in high- and medium-density cropland zones, respectively. The Cellular Automata–Markov Model shows reasonable distribution of forests. Scenarios with enhanced forest interspersion and juxtaposition metrics (75.28 to 91.12) showed reductions in TP (26.92% to 34.61%) and TN (18.45% to 25.89%) concentrations by 2025 compared to a natural economic development scenario. Landscape configuration optimization could assist managers in improving water quality.

Suggested Citation

  • Yanan Wang & Guishan Yang & Saiyu Yuan & Jiacong Huang & Hongwu Tang, 2024. "Demonstrating the Underestimated Effect of Landscape Pattern on Total Nitrogen and Total Phosphorus Concentrations Based on Cellular Automata–Markov Model in Taihu Lake Basin," Land, MDPI, vol. 13(10), pages 1-21, October.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:10:p:1620-:d:1492847
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    References listed on IDEAS

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    2. Mansour, Shawky & Al-Belushi, Mohammed & Al-Awadhi, Talal, 2020. "Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques," Land Use Policy, Elsevier, vol. 91(C).
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