Discrete Wavelet Analysis Of Dissolved Oxygen Concentration Variation Under Ice In A Frozen Lake

Dissolved oxygen is the indispensable substance of maintaining the metabolism of lives in water, the content of dissolved oxygen is an important indicator to measure the ability of water self-purification, and the concentration of dissolved oxygen is an important parameter to calculate the content of dissolved oxygen. There are so many factors influence the change of dissolved oxygen concentration. Based on a large number of researches, atmospheric pressure, gaseous oxygen in the atmosphere, photosynthesis of the hydrophyte and temperature all have a great influence on the concentration of dissolved oxygen, they lead to extremely complex changes of dissolved oxygen. However the change of dissolved oxygen under ice is different. The water is ice covered, the ice blocks the contact between the water and the atmosphere, so the atmosphere almost has no influence on the dissolved oxygen and the influence of photosynthesis is greatly reduced. Especially at high latitudes, the duration of day and night is not equal and constantly changing, and in the process of ice-out, with thinning ice, the number of influence factors is increasing, these increasing factors make the change of dissolved oxygen concentration more complex.Wavelet transform is an ideal tool for analysis of nonstational signals. In recent years, Discrete Wavelet Transform has been used successfully in many scientific and engineering applications. However applications of Discrete Wavelet Transform in the analysis of dissolved oxygen concentration variation under ice are rare. The goal of this dissertation is apply Discrete Wavelet Transform for analyzing the variation of dissolved oxygen concentration under ice, achieving the low frequency smooths and the high frequency details.Based on multi-scale analysis theory of discrete wavelet transform, decompose and reconstruct the data of dissolved oxygen concentration that is collected in Finland Valkea-kotinen under ice at measurement point No2 and Nol different depths from January 13,2011 to May 17,2011 by Daubechies wavelet series. By comparing the effects of wavelet decomposition of dbl-db7, it shows that the reconstruction results of db4 are much better. Through taking multi-scale analysis of dissolved oxygen concentration in this position at different depths by db4, it elicits the data curves of low-frequency and high-frequency reconstruction. Analyze the low frequency and high frequency curves of dissolved oxygen concentration, and the function fitting of these curves. The major contributions of this dissertation are summarized as follows:1. The slope mutation of the smooth and the significant fluctuations of the details make sure the approximate time when the ice began to melt and when the ice melt completely.2. Summarize the trends of the dissolved oxygen concentration variation at different depths of these two measurement points, the characteristics of dissolved oxygen concentration variation with depth, the particularity of dissolved oxygen concentration variation in the ice melting process.3. By comparing measurement point Nol and No2, get the characteristics of dissolved oxygen concentration variation under ice in different locations of lake.4. By fitting high frequency and low frequency curves, get the function expressions of dissolved oxygen concentration at different depths, and provide an new idea of analyzing the variation of dissolved oxygen concentration at high latitudes.