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Tytuł artykułu

Application of the Triple Diagram Method in forecasting lake water level, on the example of Lake Charzykowskie

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The work focused on forecasting changes in lake water level. The study employed the Triple Diagram Method (TDM) using geostatistical tools. TDM estimates the value by information from an earlier two periods of observation, refers as lags. The best results were obtained for data with an average a 1-week lag. At the significance level of 1σ, a the forecast error of ±2 cm was obtained. Using separate data for warm and cold months did not improve the efficiency of TDM. At the same time, analysis of observations from warm and cold months explained trends visible in the distribution of year-round data. The methodology, built on case study and proposed evaluation criteria, may function as a universal solution. The proposed methodology can be used to effectively manage water-level fluctuations both in postglacial lakes and in any case of water-level fluctuation.
Wydawca
Rocznik
Tom
Strony
11--16
Opis fizyczny
Bibliogr. 16 poz., rys., tab., wykr.
Twórcy
  • Nicolaus Copernicus University, Faculty of Earth Sciences and Spatial Management, ul. Lwowska 1, 87-100, Toruń, Poland
  • AGH University of Science and Technology, Faculty of Mine Surveying and Environmental Engineering, Krakow, Poland
Bibliografia
  • ABRAHART R.J., MOUNT N.J., SHAMSELDIN A.Y. 2012. Neuroemulation: definition and key benefits for water resources research. Hydrological Sciences Journal. Vol. 57(3) p. 407–423. DOI 10.1080/02626667.2012.658401.
  • ALTUNKAYNAK A., ÖZGER M., SEN Z. 2003. Triple diagram model of level fluctuations in Lake Van, Turkey. Hydrology and Earth System Sciences. Vol. 7(2) p. 235-244. DOI 10.5194/hess-7-235-2003.
  • ALTUNKAYNAK A. 2007. Forecasting surface water level fluctuations of Lake Van by artificial neural networks. Water Resources Management. Vol. 21(2) p. 399–408. DOI 10.1007/s11269-006- 9022-6.
  • BAJKIEWICZ-GRABOWSKA E. 2005. Jeziora. Zmiany stanów wody. W: Geografia fizyczna Polski [Lakes. Changes in water levels. In: Physical Geography of Poland]. Ed. A. Richling, K. Ostaszewska. Warszawa. Wydaw. Nauk. PWN p. 173–183.
  • BARAŃCZUK J., BOROWIAK D. 2010. Jezioro Charzykowskie. W: Atlas jezior Zaborskiego Parku Krajobrazowego [Lake Charzykowskie. In: Atlas of the Zaborski Landscape Park Lakes]. Ed. J. Barańczuk, D. Borowiak. Gdańsk, Charzykowy. Katedra Limnologii Uniwersytetu Gdańskiego; Pomorski Zespół Parków Krajobrazowych p. 32–41.
  • BUYUKYILDIZ M., TEZEL G., YILMAZ V. 2014. Estimation of the change in lake water level by artificial intelligence methods. Water Resources Management. Vol. 28(13) p. 4747–4763. DOI 10.1007/ s11269-014-0773-1.
  • CHOIŃSKI A. 2006. Katalog jezior Polski [The catalogue of Polish lakes]. Poznań. Wydaw. Nauk. UAM. ISBN 8323217327 pp. 599.
  • COULIBALY P. 2010. Reservoir computing approach to Great Lakes water level forecasting. Journal of Hydrology. Vol. 381(1) p. 76–88. DOI 10.1016/j.jhydrol.2009.11.027.
  • KISI O., SHIRI J., NIKOOFAR B. 2012. Forecasting daily lake levels using artificial intelligence approaches. Computers & Geosciences. Vol. 41 p. 169–180. DOI 10.1016/j.cageo.2011.08.027.
  • NOURY M., SEDGHI H., BABAZEDEH H., FAHMI H. 2014. Urmia lake water level fluctuation hydro informatics modeling using support vector machine and conjunction of wavelet and neural network. Water Resources. Vol. 41(3) p. 261–269. DOI 10.1134/S0097807 814030129.
  • ÖZGER M., ŞEN Z. 2007. Triple diagram method for the prediction of wave height and period. Ocean Engineering. Vol. 34(7) p. 1060– 1068.
  • PASIERBSKI M. 1975. Uwagi o genezie niecki jeziora Charzykowskiego [Remarks on the genesis of the Charzykowskie lake basin]. Acta Universitatis Nicolai Copernici. Geografia. Vol. 11 p. 101–103.
  • PIASECKI A., JURASZ J., ADAMOWSKI J.F. 2018. Forecasting surface water- level fluctuations of a small glacial lake in Poland using a wavelet- based artificial intelligence method. Acta Geophysica. Vol. 66(5) p. 1093–1107. DOI 10.1007/s11600-018-0183-5.
  • PIASECKI A., JURASZ J., WITKOWSKI W. 2019. Application of triple diagram method in medium-term water consumption forecasting. In: Infrastructure and Environment. Ed. A. Krakowiak-Bal, M. Vaverkova. Springer p. 59–66.
  • PLEWA K., WRZESIŃSKI D., BACZYŃSKA A. 2017. Przestrzenne i czasowe zróżnicowanie amplitud stanów wody jezior w Polsce w latach 1981–2015 [Spatial and temporal differentiation of the ampli-tudes of lake water levels in Poland in the years 1981–2015]. Badania Fizjograficzne. Ser. A Geografia Fizyczna. Vol. 68 p. 115–126. DOI 10.14746/bfg.2017.8.8.
  • SANIKHANI H., KISI O., KIAFAR H., GHAVIDEL S. 2015. Comparison of different data-driven approaches for modeling lake level fluctua-tions: The case of Manyas and Tuz Lakes (Turkey). Water Resources Management. Vol. 29(5) p. 1557–1574. DOI 10.1007/ s11269-014-0894-6.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-83399767-cf5e-4932-b0e4-2eca918fa26c
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