Morlet wavelet and autocorrelation analysis of long-term data series of the Kis-Balaton water protection system (KBWPS)

Abstract

Lake Balaton is the largest shallow freshwater lake in Central Europe. Its water quality is mainly affected by the supplying rivers and other water sources. The primary source is the Zala River. The water of this river used to be filtered by the Kis-Balaton wetland (KBW) before entering Lake Balaton at Keszthely Bay. In the course of the nineteenth century, water level modifications at KBW shrank and it lost its full capacity to function as a filter for the Zala's waters, so the nutrient load of Lake Balaton greatly increased, and its water quality started to deteriorate. This is the reason an artificial extended wetland called the Kis-Balaton water protection system (KBWPS) had to be constructed–to retain the inorganic nutrients at the mouth of the Zala River and stop the further degradation of Balaton's water quality. In this study, Morlet wavelet spectrum (periodicity) analysis and autocorrelation (memory) analysis were used with weekly chemical, biological and physical data for the KBWPS for the period 1993–2007. We compared the periodicity and the memory of the parameters in the two different habitats of the KBWPS and the Zala River. We also analyzed the tracking capability of the periodical seasons of the two phases (the complete Phase I, and the incomplete Phase II) and the river. The results showed that the incomplete Phase II is unable to conserve the periodicity and sustain long memory because of the shading provided by the macrophyte cover and the extra inflows. In conclusion, we were able to point out the dependence of the system's processes on temperature and climate conditions with methods that have not yet been used for this kind of purpose.