Chemical speciation of selected toxic metals and multivariate statistical techniques used to assess water quality of tropical Mexican Lake Chapala

Lake Burlan, a lentic ecosystem artificially created by untreated runoff from adjacent rice fields, is located in the Amazon region within the dry forests of northern Peru. This body of water plays a fundamental role in agriculture and recreational activities in the area, which are fundamental to the local economy. This research aimed to evaluate the water quality of Lake Burlan using the Water Quality Index of Peru (WQI-PE). In addition, both spatial and depth variations of limnological parameters and trace elements were determined. The WQI-PE was calculated at seven sampling stations at two depths (surface level and one meter), using 18 limnological parameters and nine trace elements. The WQI-PE assessment indicated that the lake water quality ranged from poor to fair for both depths. Statistical analysis showed that nine limnological parameters and five trace elements showed spatial differences across seven sampling stations, while three limnological parameters and two trace elements showed depth-dependent variations. Concentrations of arsenic, cadmium, mercury, and lead were in exceedance of the national and international standards on environmental water quality. Therefore, the water quality of Lake Burlan is affected mainly by the impact of the surrounding rice fields and recreational activities. This research establishes a starting point for future monitoring to assist in the implementation of prevention and mitigation. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-74648-2.

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Chemical speciation of selected toxic metals and multivariate statistical techniques used to assess water quality of tropical Mexican Lake Chapala

Cited by 4 publications

References 55 publications

A comprehensive review of water quality indices (WQIs): history, models, attempts and perspectives

A comprehensive review of water quality indices (WQIs): history, models, attempts and perspectives

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