Characteristics of the vertical variation in water quality indicators of aquatic landscapes in urban parks: A case study of Xinxiang, China

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Abstract

The quality of landscape water directly impacts the recreational and leisure experiences of the public. Factors such as water clarity, color, and taste can influence public perception, while contaminants like heavy metals, algae, and microorganisms may pose health risks. Stratified monitoring can reveal variations in the physical, chemical, and biological properties of water at different depths, thereby providing a more comprehensive understanding of water quality and aiding in the identification of pollution sources. This study examined aquatic landscapes at five parks in Xinxiang, China, monitoring thirteen indicators including Water Temperature (WT), Chroma (Ch), Turbidity (Tu), Suspended Solids (SS), Electrical Conductivity (EC), pH, Dissolved Oxygen (DO), Total Nitrogen (TN), Total Phosphorus (TP), Chemical Oxygen Demand (COD), Fe, Zn, and Cu. Utilizing the single-factor evaluation method, the water quality level of each indicator was assessed in accordance with the Water Quality Standard for Scenery and Recreation Area of the People’s Republic of China (GB12941-91). The findings revealed significant vertical variations in the levels of TN, TP, COD, Fe, Zn and Cu of aquatic landscapes at parks, while WT, Ch, Tu, SS, EC, and DO showed no marked differences (P>0.05). The monthly dynamics of the water quality indicators indicated generally consistent trends for WT, Ch, Tu, SS, EC, DO, TN, TP, Zn, and Cu, albeit with varying degrees of fluctuation; however, the trends for EC, pH, COD, and Fe exhibited greater variability. These results offer valuable insights for the environmental protection and management of aquatic landscapes in urban parks. Stratified monitoring can capture the dynamic changes in water quality, assisting managers in developing more effective water quality management strategies.

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Zhang, Y., Qin, W., & Qiao, L. (2024). Characteristics of the vertical variation in water quality indicators of aquatic landscapes in urban parks: A case study of Xinxiang, China. PLoS ONE, 19(12 December). https://doi.org/10.1371/journal.pone.0314860

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