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

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

Agricultural Water Management, 2022, vol. 274, issue C

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.

Keywords: Farm pond; Water quality; Structural equation modeling; Self-organizing map; Spatiotemporal variability (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378377422005005
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:agiwat:v:274:y:2022:i:c:s0378377422005005

DOI: 10.1016/j.agwat.2022.107953

Access Statistics for this article

Agricultural Water Management is currently edited by B.E. Clothier, W. Dierickx, J. Oster and D. Wichelns

More articles in Agricultural Water Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().