Statistical analysis of water quality parameters in the basin of the Nišava River (Serbia) in the period 2009–2018

Abstract

This paper analyzes water quality from four hydrological stations in the Nišava river basin from 2009–2018 based on the following parameters: pH, conductivity, O2 saturation, BOD5, suspended solids, total oxidized nitrogen, phosphates, turbidity and coliform bacteria. Authors have applied WQI (water quality index) as the most reliable indicator of the watercourses pollution for setting of surface water flow quality. Statistical analysis of variance (ANOVA) using t-test inferential statistical analysis and post-hoc Tukey test were applied to evaluate statistically significant differences between specific data groups. The results show that bad water quality was registered on all the profiles on an annual basis (WQI = 65–71). The river water pH decreases downstream, while values of BOD5, suspended solids, turbidity, TON, phosphates and coliform bacteria gradually increase. The waters of the Nišava at the station Niš belong to the third class of waters and they are mostly loaded with organic matter originating from waste sewage and industrial waters of both urban and rural areas.

Trend Analysis of Water Quality Parameters in the Middle Part of the Danube Flow in Serbia

“…Numeric characteristics of samples are representing mean annual values of the parameters, which are used for analyses and discussion of the results obtained. The methods used in this paper for statistical processing and data analysis were: − Basic statistical analysis and ANOVA [23]. − Linear regression for trend analysis [24].…”

Water quality evaluation of the Danube River basin in Bačka (northern Serbia) using multivariate statistical techniques

“…In recent years, numerous multi-criteria methods such as AHP -Analytic Hierarchy Process (Sutadian et al 2017), ANP -Analytic Network Process (Yousefi, Zahedi, Niksokhan 2018), PROMETHEE -Preference Ranking Organization Method for Enrichment Evaluation with GAIA interactive module or geometry module GAIA Analysis for interactive help have been used (Mladenović-Ranisavljević et al 2021). Apart from the mentioned statistical procedures, due to ease of use, an indicator such as WQI -Water Quality Index is often used (Stričević et al 2021). Numerous multivariate statistical techniques, such as one-factor analysis of variance (ANOVA), Pearson's correlation and principal component analysis (PCA), are the most commonly used methods in the assessment of spatiotemporal changes in water quality (Garizi, Sheikh, Sadoddin 2011;Monica, Choi 2016), as well as the main sources of pollutants (Unda-Calvo et al 2020).…”

Statistical Methods and Models for Pollutant Control in Municipal Surface Waters

“…However, not only MSTs represent the statistical studies for waters, especially surface waters. Many other statistical methods and models can be remarkably cited in this kind of analysis, as in the papers of Mohammed et al [19], Bărbulescu et al [20], Schreiber et al [21], Kovrov et al [22], Antonopoulos et al [23], Majerek et al [24], Stričević et al [25], Khouri et al [26], Bhat et al [27], and Le et al [28].…”