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<p>Buriganga is a significant river in Dhaka that is surrounded by several industries, and comprehensive research has been conducted on it owing to excessive pollution and its effects on the environment’s health. However, there is a noticeable research gap in long-term integrative statistical analysis and monitoring with seasonal variations. The novelty of this study is to assess the variation and internal relationship of parameters with seasonal changes in water quality. Seven crucial locations were chosen to collect samples in the wet season of 2023 and the dry season of 2024. The dataset demonstrated good reliability (Cronbach’s alpha = 0.826) and reasonable sampling adequacy (KMO = 0.670, p &lt; 0.001). While dissolved oxygen (DO) and temperature were higher during the wet season, the dry season recorded higher concentrations of biochemical oxygen demand (BOD), chemical oxygen demand (COD), total dissolved solids (TDS), total suspended solids (TSS), and turbidity (mean COD: 299.88 mg/L, BOD: 21.79 mg/L, TDS: 628.41 mg/L, TSS: 667.35 mg/L, turbidity: 51.16 NTU). The greatest seasonal variations were found in TSS (128 ± 1040 mg/L) and electrical conductivity (EC: 288 ± 1142 µS/cm). Correlation analysis revealed the strongest positive relationship between EC and turbidity (0.935) and the strongest negative relationship between BOD and DO (-0.949). The principal component analysis (PCA) revealed a negative loading factor for DO and temperature of -0.864, while a positive factor was observed for turbidity of 0.9327 and TSS of 0.980, with cluster analysis revealing the maximum distance between pH and TDS. This study demonstrated that the Buriganga River is insufficient to support a feasible river ecosystem and requires proper wastewater management and a long-term integrated plan to reduce the difficulties.</p>

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Multivariate statistical approach to evaluating seasonal hydrochemistry of surface water in the Buriganga River

  • 期刊论文

  • 发表日期：

    2025年7月9日

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  • Md. Abdullah Al Arafat,
  • Md. Rubel Thakur,
  • Obaedul Karim,
  • Md. Zakir Hossain,
  • Rubinoor Islam Swarna

摘要

Buriganga is a significant river in Dhaka that is surrounded by several industries, and comprehensive research has been conducted on it owing to excessive pollution and its effects on the environment’s health. However, there is a noticeable research gap in long-term integrative statistical analysis and monitoring with seasonal variations. The novelty of this study is to assess the variation and internal relationship of parameters with seasonal changes in water quality. Seven crucial locations were chosen to collect samples in the wet season of 2023 and the dry season of 2024. The dataset demonstrated good reliability (Cronbach’s alpha = 0.826) and reasonable sampling adequacy (KMO = 0.670, p < 0.001). While dissolved oxygen (DO) and temperature were higher during the wet season, the dry season recorded higher concentrations of biochemical oxygen demand (BOD), chemical oxygen demand (COD), total dissolved solids (TDS), total suspended solids (TSS), and turbidity (mean COD: 299.88 mg/L, BOD: 21.79 mg/L, TDS: 628.41 mg/L, TSS: 667.35 mg/L, turbidity: 51.16 NTU). The greatest seasonal variations were found in TSS (128 ± 1040 mg/L) and electrical conductivity (EC: 288 ± 1142 µS/cm). Correlation analysis revealed the strongest positive relationship between EC and turbidity (0.935) and the strongest negative relationship between BOD and DO (-0.949). The principal component analysis (PCA) revealed a negative loading factor for DO and temperature of -0.864, while a positive factor was observed for turbidity of 0.9327 and TSS of 0.980, with cluster analysis revealing the maximum distance between pH and TDS. This study demonstrated that the Buriganga River is insufficient to support a feasible river ecosystem and requires proper wastewater management and a long-term integrated plan to reduce the difficulties.