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Effects of environmental and agronomic factors on pond water quality within an intensive agricultural landscape in subtropical southern China

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  • Meng, Cen
  • Liu, Huanyao
  • Li, Yuyuan
  • Shen, Jianlin
  • Li, Xi
  • Wu, Jinshui

Abstract

Water quality deterioration, such as eutrophication, can contribute to the degradation of farm pond ecosystems, threatening numerous ecological services and socioeconomic benefits. However, the variability of water quality and the complexity of influencing variables pose large uncertainties for pond management practices and watershed planning. This study integrated a self-organizing map (SOM) and partial least squares structural equation modeling (PLS-SEM) to evaluate the nitrogen (N) and phosphorus (P) variations in 39 typical farm ponds in the Dongting Lake basin, and related the variations to pond internal factors, external environment, and agronomic management. The results indicated that 39 monitored farm ponds faced a high risk of eutrophication owing to high N and P levels, and that total N (TN), total P (TP), and particulate P (PP) generally exceeded the threshold of level V surface water quality standards in China (2.0 mg N L−1 and 0.2 mg P L−1). Simultaneously, pond water quality showed high spatiotemporal variability, and pollution hotspots occurred mostly during the overlapping periods of fallow-dry-winter and planting-rainy-spring. Based on the constructed SEM model, external environmental factors (meteorology, catchment landscape composition, configuration, topography, and soil chemical properties), pond internal characteristics, and agronomic management combined explained 60.2 ± 2.9 % and 54.2 ± 3.1 % of the N and P variations, respectively. There were intricate interactions among the above latent variables, including such meteorology positively moderated the paths of soil chemical properties→pond P and landscape composition→pond N and P; landscape composition, soil, and pond internal characteristics mediated the effects of other variables on variations of N and P. The total effects (indirect effects + direct effects) of landscape composition on the variations of pond N and P were higher than those of other variables. Among all the indicators composing latent variables, agricultural and residential land area percentage, rainfall, water depth, and fish farming were relatively important in pond water quality variations. The constructed model and analytical results offer essential information for the accurate management and restoration of pond water quality.

Suggested Citation

  • Meng, Cen & Liu, Huanyao & Li, Yuyuan & Shen, Jianlin & Li, Xi & Wu, Jinshui, 2022. "Effects of environmental and agronomic factors on pond water quality within an intensive agricultural landscape in subtropical southern China," Agricultural Water Management, Elsevier, vol. 274(C).
    • Handle: RePEc:eee:agiwat:v:274:y:2022:i:c:s0378377422005005
    DOI: 10.1016/j.agwat.2022.107953
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    References listed on IDEAS

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    1. Zhang, Wangshou & Li, Hengpeng & Pueppke, Steven G & Diao, Yaqin & Nie, Xiaofei & Geng, Jianwei & Chen, Dongqiang & Pang, Jiaping, 2020. "Nutrient loss is sensitive to land cover changes and slope gradients of agricultural hillsides: Evidence from four contrasting pond systems in a hilly catchment," Agricultural Water Management, Elsevier, vol. 237(C).
    2. Arnold Wollenberg, 1977. "Redundancy analysis an alternative for canonical correlation analysis," Psychometrika, Springer;The Psychometric Society, vol. 42(2), pages 207-219, June.
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    1. Yihan Wu & Fucang Qin & Xiaoyu Dong & Long Li, 2024. "Modelling Ecological Hazards and Causal Factors in the Yellow River Basin’s Key Tributaries: A Case Study of the Kuye River Basin and Its Future Outlook," Sustainability, MDPI, vol. 16(16), pages 1-34, August.

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