Wavelet and statistical analyses of river water quality parameters: a case study in the Lower Minnesota River

Abstract

Abstract Statistical and wavelet analyses are useful tools for analyzing river water quality parameters. In this study, they were employed to study parameters including biochemical oxygen demand (BOD), dissolved oxygen (DO), nitrate (NO3), ammonium (NH4), phosphate (PO4), total phosphorus (TP), total Kjeldahl nitrogen (TKN), chlorophyll a (CHLA), total suspended solids (TSS) and water temperature (TEMP) monitored at five hydrologic stations on the Lower Minnesota River, USA. Strong positive correlations were observed between CHLA-BOD, TP-TKN, TP-TSS and TKN-TSS, with strong negative correlation between DO-TEMP. Daubechies wavelet at level 5 has been calculated for some key water quality parameters as it gives the finer scale approximation and decomposition of each water parameter. The results show that TEMP and DO have relative quasi-periodicity of about one year, while the quasi-periodicity of NH4 and PO4 are weaker than for TEMP and DO. Correlations between some parameters based on wavelet decomposition results are consistent. The fluctuation range characteristics of some parameters were also analyzed through wavelet decomposition.