Advertisement

Water Resources Management

, Volume 29, Issue 14, pp 5275–5294 | Cite as

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

  • József Kovács
  • Solt Kovács
  • István Gábor Hatvani
  • Norbert Magyar
  • Péter Tanos
  • János Korponai
  • Alfred Paul Blaschke
Article

Abstract

Monitoring systems in general have to meet numerous requirements, the most important of which are representativeness and cost efficiency. The aim of the study, therefore, was to present the spatial optimization of the monitoring networks of a river (the Danube), a wetland-lake system (Kis-Balaton & Lake Balaton), and a sub-surface water system in the watershed of Lake Neusiedl/Fertő over a period of approximately two decades using a novel method, Combined cluster and discriminant analysis (CCDA). In the case of the river the results show that the monitoring network yields redundant information on certain sections, so that of 12 sampling sites 3 can be discarded. It was not, however, enough to consider just the tributaries when it comes to optimization. In the case of the wetland (Kis-Balaton) one pair of sampling sites out of 12, while in the case of Lake Balaton 5 out of 10 can be abandoned. For the sub-surface water system, however, all the 50 sites contained exclusive information; hence, all of these were shown to be necessary. In addition, neighboring sampling sites were compared pairwise using CCDA and the corresponding results were visualized in diagrams or so called “difference maps” indicating the location of the biggest differences. This approach also indicates the researcher where to place new sampling sites should the possibility arise. The discussed methodology proved to be highly useful in the optimization of the monitoring networks of the presented water systems.

Keywords

Classification into homogeneous groups CCDA R package Downsizing Environmental monitoring system optimization Water quality 

Notes

Acknowledgments

The authors would like to give thanks to the Austrian Federal Ministry of Agriculture, Forestry, Environment and Water Management, Department VII/Unit 1 National Water Management for the dataset of the Seewinkel and to the “Lendület” program of the MTA (LP2012-27/2012) & the TÁMOP-4.2.2.B-15/1/KONV-2015-0004) project of the Pannon University for the support.

References

  1. Astel A, Biziuk M, Przyjazny A, Namieśnik J (2006) Chemometrics in monitoring spatial and temporal variations in drinking water quality. Water Res 40:1706–1716CrossRefGoogle Scholar
  2. Barca E, Calzolari MC, Passarella G, Ungaro F (2013) Predicting shallow water table depth at regional scale: optimizing monitoring network in space and time. Water Resour Manag 27:5171–5190Google Scholar
  3. Barca E, Passarella G, Vurro M, Morea A (2015) MSANOS: data-driven, multi-approach software for optimal redesign of environmental monitoring networks. Water Resour Manag 29:619–644CrossRefGoogle Scholar
  4. Blaschke AP, Gschöpf C (2011) Grundwasserströmungsmodell Seewinkel. Endbericht, EisenstadtGoogle Scholar
  5. Burton I (1987) Report on reports: our common future. Environ Sci Policy Sustain Dev 29:25–29CrossRefGoogle Scholar
  6. Casper AF, Dixon B, Steimle ET, Hall ML, Conmy RN (2012) Scales of heterogeneity of water quality in rivers: Insights from high resolution maps based on integrated geospatial, sensor and ROV technologies. Appl Geogr 32:455–464CrossRefGoogle Scholar
  7. Chen Q, Wu W, Blanckaert K, Ma J, Huang G (2012) Optimization of water quality monitoring network in a large river by combining measurements, a numerical model and matter-element analyses. J Environ Manag 110:116–124CrossRefGoogle Scholar
  8. Chilundo M, Kelderman P, O’keeffe J (2008) Design of a water quality monitoring network for the Limpopo river basin in Mozambique. Physics and Chemistry of the Earth, Parts A/B/C, 33:655–665Google Scholar
  9. European Council (2000) Directive 2000/60/EC of the European parliament and of the council establishing a framework for community action in the field of water policy, BrusselsGoogle Scholar
  10. Ferreyra RA, Apezteguía HP, Sereno R, Jones JW (2002) Reduction of soil water spatial sampling density using scaled semivariograms and simulated annealing. Geoderma 110:265–289CrossRefGoogle Scholar
  11. Gomes AI, Pires JC, Figueiredo SA, Boaventura RA (2014) Optimization of river water quality surveys by multivariate analysis of physicochemical, bacteriological and ecotoxicological data. Water Resour Manag 28:1345–1361CrossRefGoogle Scholar
  12. Hatvani IG (2014) Application of state-of-the-art geomathematical methods in water protection: − on the example of the data series of the Kis-Balaton Water Protection System. Ph.D., Eötvös Loránd University [in English]Google Scholar
  13. Hatvani IG, Kovács J, Kovács ISZ, Jakusch P, Korponai J (2011) Analysis of long-term water quality changes in the Kis-Balaton water protection system with time series-, cluster analysis and Wilks’ lambda distribution. Ecol Eng 37:629CrossRefGoogle Scholar
  14. Hatvani I, Magyar N, Zessner M, Kovács J, Blaschke A (2014a) The water framework directive: can more information be extracted from groundwater data? A case study of Seewinkel, Burgenland, eastern Austria. Hydrogeol J 22:779–794CrossRefGoogle Scholar
  15. Hatvani IG, Clement A, Kovács J, Kovács ISZ, Korponai J (2014b) Assessing water-quality data: the relationship between the water quality amelioration of Lake Balaton and the construction of its mitigation wetland. J Great Lakes Res 40:115–125CrossRefGoogle Scholar
  16. Hatvani IG, Kovács J, Márkus L, Clement A, Hoffmann R, Korponai J (2015) Assessing the relationship of background factors governing the water quality of an agricultural watershed with changes in catchment property (W-Hungary). J Hydrol 521:460CrossRefGoogle Scholar
  17. Højberg A, Troldborg L, Nyegaard P, Ondracek M, Stisen S (2009) Handling and linking data and hydrological models–experiences from the Danish national water resources model (DK-model). http://vandmodel.dk/xpdf/hoejberg_et_al_modelcare2009.pdf Accessed 01 Sept 2015
  18. Kennedy CD, Genereux DP, Mitasova H, Corbett DR, Leahy S (2008) Effect of sampling density and design on estimation of streambed attributes. J Hydrol 355:164–180CrossRefGoogle Scholar
  19. Korponai J, Braun M, Buczkó K, Gyulai I, Forró L, Nédli J, Papp I (2010) Transition from shallow lake to a wetland: a multi-proxy case study in Zalavári pond, Lake Balaton, Hungary. Hydrobiologia 641:225–244CrossRefGoogle Scholar
  20. Kovács J, Korponai J, Kovács ISZ, Hatvani IG (2012a) Introducing sampling frequency estimation using variograms in water research with the example of nutrient loads in the Kis-Balaton water protection system (W Hungary). Ecol Eng 42:237–243CrossRefGoogle Scholar
  21. Kovács J, Nagy M, Czauner B, Kovács ISZ, Borsodi AK, Hatvani IG (2012b) Delimiting sub-areas in water bodies using multivariate data analysis on the example of Lake Balaton (W Hungary). J Environ Manag 110:151–158CrossRefGoogle Scholar
  22. Kovács J, Kovács S, Magyar N, Tanos P, Hatvani IG, Anda A (2014) Classification into homogeneous groups using combined cluster and discriminant analysis. Environ Model Softw 57:52–59CrossRefGoogle Scholar
  23. Kovács J, Márkus L, Szalai J, Kovács ISZ (2015) Detection and evaluation of changes induced by the diversion of river Danube in the territorial appearance of latent effects governing shallow-groundwater fluctuations. J Hydrol 520:314–325CrossRefGoogle Scholar
  24. Kroiss H, Matsche N, Vogel B, Zessner M, Kavka GG, Farnleitner AH, Mach RL, Gutknecht D, Blaschke A, Heinecke U, Hütter T, Sengschmitt D, Steiner KH (2002) Auswirkungen der Versickerung von biologisch gereinigtem Abwasser auf das Grundwasser. Report for BuMi Wirtschaft u. Arbeit, BuMi Bildung Wissenschaft u. Kultur, BuMi Land- Forstwirtschaft, Umwelt und Wasserwirtschaft, Amt der Burgenländischen Landesregierung Abteilung 9Google Scholar
  25. Kroiss H, Zessner M, Schilling C, Blaschke A, Asztalos J, Kirnbauer RW, Tentschert EH, Hassler C, Kavka G, Farnleitner AH, Mach RL (2004) Auswirkung von Versickerung und Verrieselung von durch Kleinkläranlagen mechanisch biologisch gereinigtem Abwasser in dezentralen Lagen, Phase I, EndberichtGoogle Scholar
  26. Lotz G (1988) A Kis-Balaton vízvédelmi rendszer. Hidrológiai Tájékoztató 28(2):20–22Google Scholar
  27. Magyar N, Hatvani IG, Kovácsné ISZ, Herzig A, Dinka M, Kovács J (2013a) Application of multivariate statistical methods in determining spatial changes in water quality in the Austrian part of Neusiedler See. Ecol Eng 55:82–92Google Scholar
  28. Magyar N, Trásy B, Kutrucz GY, Dinka M (2013b) Delineating water bodies on the Hungarian side of Lake Fertő/Neusiedler See. In: Geiger J, Pál-Molnár E, Malvić T (eds) Theories and applications in geomathematics: selected studies of the 2012 Croatian-Hungarian Geomathematical Convent, Opatija, p 161Google Scholar
  29. Padisák J, Reynolds C (2003) Shallow lakes: the absolute, the relative, the functional and the pragmatic. Hydrobiologia 506–509:1–11CrossRefGoogle Scholar
  30. Popescu I, Cioaca E, Pan Q, Jonoski A, Hanganu J (2015) Use of hydrodynamic models for the management of the Danube delta wetlands: the case study of Sontea-Fortuna ecosystem. Environ Sci Pol 46:48–56CrossRefGoogle Scholar
  31. Sharp WE (1971) A topologically optimum water-sampling plan for rivers and streams. Water Resour Res 7:1641–1646CrossRefGoogle Scholar
  32. Tanos P, Kovács J, Kovács S, Anda A, Hatvani IG (2015) Optimization of the monitoring network on the River Tisza (Central Europe, Hungary) using combined cluster and discriminant analysis, taking seasonality into account. Environ Monit Assess 187:575. doi: 10.1007/s10661-015-4777-y
  33. Wu W, Chen Q, Li J, Chen G (2010) Optimization of river water quality monitoring sections. Acta Sci Circumst 30:1537–1542Google Scholar
  34. Zhouhu W, Jian Z, Jie Z, Jie R, Shan C (2011) A monitoring project planning technique of the water quality spatial distribution in Nansi lake. Procedia Environ Sci 10 C 2320–2328Google Scholar
  35. Zlinszky A, Timár G (2013) Historic maps as a data source for socio-hydrology: a case study of the Lake Balaton wetland system, Hungary. Hydrol Earth Syst Sci 17:4589–4606CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Department of Physical and Applied GeologyEötvös Loránd UniversityBudapestHungary
  2. 2.Institute for Geological and Geochemical ResearchMTA Research Centre for Astronomy and Earth SciencesBudapestHungary
  3. 3.Department of Meteorology and Water Management, Georgikon FacultyUniversity of PannoniaKeszthelyHungary
  4. 4.Department Kis-BalatonWest Transdanubian Water AuthorityKeszthelyHungary
  5. 5.Department of Chemistry and Environmental SciencesUniversity of West HungarySzombathelyHungary
  6. 6.Institute of Hydraulic Engineering and Water Resources ManagementVienna University of TechnologyWienAustria
  7. 7.Currently an M.Sc. student in Mathematics at ETH ZürichZürichSwitzerland

Personalised recommendations