ArticleEnvironmental monitoring and assessment2021
Multivariate analysis of water quality parameters in Lake Palic, Serbia.
Article in Environmental monitoring and assessment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advancements in Monitoring Water Quality Based on Various Sensing Methods: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- Rapid Triage of Children with Suspected COVID-19 Using Laboratory-Based Machine-Learning Algorithms.Viruses · 2023Article
- Clinical Hematochemical Parameters in Differential Diagnosis between Pediatric SARS-CoV-2 and Influenza Virus Infection: An Automated Machine Learning Approach.Children (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study presents a comprehensive investigation of water quality parameters in the fourth sector of Lake Palic in Serbia, which has a regional strategic importance. Namely, it is designated as a tourist destination. What is perhaps even more important is that its surplus water ends up in Lake Ludas, a significant habitat for migrating and aquatic bird species, and it is a RAMSAR site. The conducted analysis points to the major conclusion that the reasons for very high Chlorophyll-a values can be found in considerable anthropogenic pressures exerted on the studied area. Due to these pressures, the lake is not in ecological equilibrium. To support this conclusion, an in-depth analysis was conducted using water quality measurements for 9 years, from 2011 to 2019. The data was subject to principal component analysis (PCA) and machine learning classification algorithms that identified a seasonal character regarding the lake's water quality. Water quality indexes (WQI) were determined using two approaches to provide a more general insight into the lake's overall quality. Keeping in mind the large number of data gathered monthly within the Palic-Ludas Lake system, fitted models for estimating certain water quality parameters were also developed. This was accomplished via multivariate regression, resulting in a number of equations that can, using a few basic input parameters, predict values of ammonium nitrogen, Chlorophyll-a, and 5-day biological oxygen demand. The fitted models were obtained for relatively homogeneous periods within a year identified by cluster analysis.
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Registered trials
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