Abstract
There are numerous streamwater parameters that exhibit a diurnal cycle. However, the shape of this cycle has a huge variation from one parameter to another and from one monitoring point to another on the same river. Important variations also occur at the same point during some events, such as high waters. Water level, specific conductivity, dissolved oxygen, oxidation reduction potential, and pH of the Suceava River were monitored for 365 days (2018–2019, hourly sampling frequency) in order to assess the upstream-downstream changes in the diurnal cycle of these parameters, some of these changes being caused by the impact of Suceava city, which is located between the selected monitoring points. The multiresolution analysis of the maximal overlap discrete wavelet transform and the wavelet coherence analysis were combined in a flexible methodology that helped in comparing the upstream and downstream shapes of the diurnal cycle. The methodology allowed for a fast comparison of diurnal profiles during periods of high waters or baseflow. Notable changes were observed in the moments of diurnal maxima and minima.
Highlights
The wavelet analysis of streamwater parameters has become more and more popular in the last two decades due to the advantages of this method for the study of non-linear processes [1,2]
The analysis of the major convolutions/waves of water level during a year led us to select two subsets of time series that should serve as relevant case studies of changes in diurnal profiles depending on water level variability
The choice of decomposition level depends on the user/author [32], as it is the choice of applying the multiresolution analysis only on the water level or on other parameter/all parameters
Summary
The wavelet analysis of streamwater parameters has become more and more popular in the last two decades due to the advantages of this method for the study of non-linear processes [1,2]. Wavelet analysis techniques were applied mostly on stage or discharge time series due to the wide availability of this type of data [3]. It is in the last decade when water quality parameters were involved intensively in wavelet analyses [4,5]. 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]. Urban wastewater treatment plants can alter the diurnal profile of a streamwater chemistry parameter [9,10]
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