Abstract
<title>Abstract</title> <p>The physicochemical properties of tropical river systems are strongly influenced by the seasonality of rainfall, in terms of dilution, surface runoff and wash-off of both organic and inorganic loads. The relationship between monthly rainfall and five water quality parameters (pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), total dissolved solids (TDS) and chemical oxygen demand (COD)) is investigated at Meghna Ghat station of the Meghna River in Bangladesh by plotting monthly water quality data from the Bangladesh Department of Environment (DoE) against monthly rainfall data from the NASA Prediction Of Worldwide Energy Resources (POWER) database for the year 2023. Due to the suboptimal monitoring coverage of the DoE, only data from 6 months (January, March, July, September, October and November) were used in quantitative analysis and were kept for that purpose (n = 6). Pearson correlation results indicated that there was a very strong and positive correlation between rainfall and COD (r = 0.99, p < 0.001), and moderate and negative correlation between rainfall and BOD (r = − 0.71) and TDS (r = − 0.62) respectively suggesting a combined dilution-wash off effect. At this sample size, there was no statistically significant monotonic relationship between a composite Water Quality Index (WQI) and rainfall (r = − 0.46, p = 0.36). The first two principal components from a principal component analysis (PCA) of the standardized data for the six-month period explained 85.3% of the total variance and the first principal component had strong loading for rainfall and COD, as well as BOD and TDS, indicating that the data was consistent with the correlation-based evidence for a mixed dilution–wash-off response. Because of the small number of complete monthly observations, the results are not presented as a scientific characterization of short-term rainfall – water quality dynamics but as a preliminary baseline to help develop a hypothesis, and the study explicitly notes the statistical limitations due to the small sample size.</p>