Spatial Optimization of Monitoring Networkson the Examples of a River, a Lake-Wetland System and a Sub-Surface Water System

Kovács, József; Kovács, Solt; Hatvani, István Gábor; Magyar, Norbert; Tanos, Péter; Korponai, János; Blaschke, Alfred Paul

doi:10.1007/s11269-015-1117-5

Cited by 23 publications

(24 citation statements)

References 25 publications

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“…For a detailed description of the method, see Kovács et al (2014) and the corresponding R package ("ccda", http://cran.r-project.org/web/packages/ ccda/) used for the computations. It has to be underlined that CCDA is generally applicable for many types of data, be they water chemistry data originating from surface (lake, wetland, river), subsurface water systems (the watershed of a steppe lake; Kovács et al 2015).…”

Section: Methodsmentioning

confidence: 99%

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

Tanos

Kovács

et al. 2015

Environ Monit Assess

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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.

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Section: Methodsmentioning

confidence: 99%

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

Tanos

Kovács

et al. 2015

Environ Monit Assess

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“…This is a widely known multivariate classification method in which each case starts in a separate cluster and joins up to the other clusters as the linkage distance grows, until only one cluster remains [41]. This method has been successfully applied in hydrology [42][43][44][45], hydrogeology [46], geology [47][48][49][50][51], chemistry [52] and anthropology [53] to find similar and homogeneous groups of observations. The validity of the groupings was verified using linear discriminant analysis (LDA), which separates the observations with linear planes resulting in a percentage of correctly classified cases [54,55].…”

Section: Discussionmentioning

confidence: 99%

Effects of the introduction of pre-treated wastewater in a shallow lake reed stand

et al. 2016

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Reed stands may be employed in the amelioration of water quality or even in the treatment of wastewater. In this study, the nutrient concentrations of (i) the above- and below-ground Common Reed (Phragmites australis) biomass, and (ii) surface and interstitial water were analyzed in a natural stand used in wastewater treatment. The reed stand was located in Hungarian part of Lake Fertő/Neusiedler See, by the shore near Fertőrákos Bay. The nitrate, phosphate and dissolved organic nitrogen concentrations of surface water were found to be higher on the inlet side of the reed stand compared to the outlet. The N and P concentrations in the above-ground biomass and P concentrations in the below-ground biomass increased after the introduction of pre-treated wastewater. The inter-annual differences in the characteristics of sediment interstitial water and in the nutrient content of reed tissues were assessed using statistical methods. The samples taken before and after the introduction of the pre-treated wastewater in the parcel formed different clusters. The results of the study provide further evidence that the nutrient retention capacity of natural stands of P. australis may be employed in the treatment of wastewater while protecting and preserving the valuable natural assets of the lake.

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“…. ,SG 5 still had to be examined sepa- 4 ={RH} cannot be further subdivided, they form separate groups alone. For SG 1 , CCDA suggested that no more division is needed, because of a negative difference value (d=−8.33%) for the case of division into two groups.…”

Section: The Quantitative Composition Of the Clast Typesmentioning

confidence: 99%

“…The result is a spatial pattern which shows the relationship of the sampling sites (homogeneity or difference and in particular the rate of the latter). This method has been used successfully for hydrological and hydrogeological interpretation [3][4][5] and biological analysis [6]. In this paper, CCDA is used in a sedimentological problem.…”

Section: Introductionmentioning

confidence: 99%

Interpretation of sedimentological processes of coarse-grained deposits applying a novel combined cluster and discriminant analysis

Farics

Kovács

et al. 2017

Open Geosciences

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Abstract:The main aim of this paper is to determine the depositional environments of an Upper-Eocene coarsegrained clastic succession in the Buda Hills, Hungary. First of all, we measured some commonly used parameters of samples (size, amount, roundness and sphericity) in a much more objective overall and faster way than with traditional measurement approaches, using the newly developed Rock Analyst application. For the multivariate data obtained, we applied Combined Cluster and Discriminant Analysis (CCDA) in order to determine homogeneous groups of the sampling locations based on the quantitative composition of the conglomerate as well as the shape parameters (roundness and sphericity). The result is the spatial pattern of these groups, which assists with the interpretation of the depositional processes. According to our concept, those sampling sites which belong to the same homogeneous groups were likely formed under similar geological circumstances and by similar geological processes. In the Buda Hills, we were able to distinguish various sedimentological environments within the area based on the results: fan, intermittent stream or marine.

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Spatial Optimization of Monitoring Networkson the Examples of a River, a Lake-Wetland System and a Sub-Surface Water System

Cited by 23 publications

References 25 publications

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

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

Effects of the introduction of pre-treated wastewater in a shallow lake reed stand

Interpretation of sedimentological processes of coarse-grained deposits applying a novel combined cluster and discriminant analysis

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