Wavelet Characteristics of Hydrological and Dissolved Oxygen Time Series in a Lowland River

Abstract

A b s t r a c tIn this study, we investigated the temporal variability of dissolved oxygen and water temperature in conjunction with water level fluctuations and river discharge in the Narew lowland river reach. For this purpose, high resolution hydrologic and water quality time series have been used. Spectral analyses of time series using continuous wavelet transform scheme have been applied in order to identify characteristic scales, its duration, and localisation in time. The results of wavelet analysis have shown a great number of periodicities in time series at the inter-annual time scale when compared to the classical Fourier analysis. Additionally, wavelet coherence revealed the complex nature of the relationship between dissolved oxygen and hydrological variables dependent on the scale and localisation in time. Hence, the results presented in this paper may provide an alternative representation to a frequency analysis of time series.

A Methodology for the Fast Comparison of Streamwater Diurnal Cycles at Two Monitoring Points

“…Wavelet coherence analyses are not useful only for studying the relationship between two points, but also for investigating the inter-parametric links at the same monitoring point [7]. Climate indices and water quality parameters can also be used for wavelet coherence analyses [34].…”

“…Some physical and chemical properties of streamwaters are proper indicators of water quality and can be used to trace the environmental impact of man. The specific conductivity, dissolved oxygen, oxidation reduction potential (ORP), and pH of a river water can be used to indicate the impact of urban areas on the environment and are sometimes included in wavelet analyses [5][6][7]. Cities modify the properties of natural waters through various active or passive processes, such as the discharge of stormwater runoff or the creation of an urban heat island, which has multiple effects on urban waters [8].…”

Forecasting surface water-level fluctuations of a small glacial lake in Poland using a wavelet-based artificial intelligence method

“…From a historical point of view, wavelets are new as a mathematical tool, but have their mathematical roots in the works of Joseph Fourier . Recently, studies incorporating wavelets have been conducted in the areas of hydrology (Lafrenière and Sharp 2003;Rajwa-Kuligiewicz et al 2016); manufacturing processes/fault detection (Kasashima et al 1995;Jin and Shi 2001); signal processing (Sundararajan 2015); medicine (Faust et al 2015); forecasting (Chaturvedi et al 2015); and power loads (Jurasz and Mikulik 2016); among others. Multiresolution analysis techniques, such as the wavelet transform (WT), which are widely employed in science and engineering, have received very little attention in water-level forecasting.…”

Integrated Hydraulic Modelling, Water Quality Modelling and Habitat Assessment for Sustainable Water Management: A Case Study of the Anyang-Cheon Stream, Korea

“…Fourier analysis is generally used to predict various time series changes in the environment, but it is known that there is a problem in predicting time series analysis and trends. Therefore, recently, various environmental signals have been analyzed through wavelet analysis, and it is applied to various fields [29,30]. However, most previous physical habitat simulations have not taken integrating hydraulic, water quality, and habitat simulations into account when assessing the effect that the ecological river restoration project has on the aquatic habitat.…”