Optimization of the monitoring network on the River Tisza (Central Europe, Hungary) using combined cluster and discriminant analysis, taking seasonality into account

Abstract

The most essential requirement for water management is efficient and informative monitoring. Operating water quality monitoring networks is a challenge from both the scientific and economic points of view, especially in the case of river sections ranging over hundreds of kilometers. Therefore, spatio-temporal optimization is vital. In the present study, the optimization of the monitoring system of the River Tisza, the second largest river in Central Europe, is presented using a generally applicable and novel method, combined cluster and discriminant analysis (CCDA). This area for the study was chosen because, spatial inhomogeneity of a river's monitoring network can more easily be studied in a mostly natural watershed - as in the case of the River Tisza - since the effects of man-made obstacles: e.g water barrage systems, hydroelectric power plants, artificial lakes, etc. are more pronounced. Furthermore, since the temporal sampling frequency was bi-weekly, the opportunity of optimizing the monitoring system on a temporal (monthly) scale arose. In the research, 15 water quality parameters measured at 14 sampling sites in the Hungarian section of the River Tisza were assessed for the time period 1975-2005. First, four within-year sections ("hydrochemical seasons") were determined, characterized with unequal lengths, namely 2, 4, 2, and 4 months long starting with spring. Homogeneous groups of sampling sites were determined in space for every season, with the main separating factors being the tributaries and man-made obstacles. Similarly, an overall pattern of homogeneity was determined. As an overall result, the 14 sampling sites could be grouped into 11 homogeneous groups leading to the possibility of reducing the number of sampling locations and thus making the monitoring system more cost-efficient.

Assessment of the interaction between surface- and groundwater after the diversion of the inner delta of the River Danube (Hungary) using multivariate statistics

“…7. With cluster analysis, not only similar sampling sites , but time segments of similarly behaving time points can be formed (Tanos et al 2015). It may be supposed that the years with average flow will group into similar time segments, interrupted by the large floods.…”

Periodic signals of climatic variables and water quality in a river – eutrophic pond – wetland cascade ecosystem tracked by wavelet coherence analysis

“…Ecological Indicators 83 (2017) 21-31; http://dx.doi.org/10.1016/j.ecolind.2017.07.018 Since the water coming from the River Zala passes through the different ecosystems (habitats) of the KBWPS and changes into lake water, it is suspected that hydrochemical seasonality (Kolander and Tylkowski, 2008;Tanos et al, 2015) -governed mainly by temperature driving the dynamics of biological processes -will be present/corrupted to a different degree in the various habitats mirroring their local characteristics. This is the particular process that is investigated in the present study with state-of-the-art statistical tools using the key link between hydrochemical seasonality and the periodicity of the water quality parameters.…”

Developments in water quality monitoring and management in large river catchments using the Danube River as an example

“…When monitoring a water body, the basic infrastructure and personnel have to be available at all times, even if there is only one functioning sampling site. Nevertheless, if each sampling site is managed by a different authority, equipped with their own instrumentation and personnel, the ratio of sites abandoned will equal the ratio of money saved for a direct example on the Danube and its tributary the Raab, along with an expanded discussion on the topic, see the Appendix A or for further examples see Kovács et al (2015a,b) and Tanos et al (2015).…”