Ain Shams Engineering Journal (Apr 2024)
Statistical analysis for water quality data using ANOVA (Case study – Lake Burullus influent drains)
Abstract
Lake Burullus is considered one of the most valuable northern lakes in Egypt due to its unique ecological system and special location. Over the past four decades, the lake has suffered from high contamination levels due to expansion in fish farming and increasing of agricultural drainage water entering the southern side of the lake through eight influent drains. This research aims to assess the current situation of the lake’s influent drains. For this purpose, two types of statistical analysis, Mean average method, and Analysis of Variance (ANOVA) were used. The water quality conditions for six major drains (Therah (Tira), Nashart, Zaghloul drain, Drain 7, Drain 8, and Drain 11) have been evaluated with respect to the limits of the Egyptian regulations (law No. 48/1982). First drain chemical pollution index (DCPI) was used to classify the influent drains categories (from excellent to bad) with respect to the water quality conditions. After that the hotspots for domestic, industrial wastewater and agricultural drainage water have been specified using ANOVA. The analysis was conducted using the data compiled during 2018, 2019, and 2020 for six main parameters (BOD, DO, NH4, NO3, TSS, and TDS). The results show that Nashart, Tira and Zaghloul drains should have priority to be treated due to their relatively bad water quality conditions and Nashart drain is considered the worst of them. Also, the comparison between the Mean average statistical analysis method and one-way ANOVA shows that ANOVA is more reliable because it considers many parameters at the same time plus considering the frequency trend. the adopted approach and techniques in this study can help the decision makers in setting the priorities for the rehabilitation projects of the agricultural drains in Egypt.
