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Application of the maxima distribution to the evaluation of the variability of flood risks in the Odra River basin on the basis of quarterly maxima of daily water levels

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The method of assessing the flood risk variability has been presented based on maximum value distributions. Hydrological data were used in the form of daily water levels for the period 1981-2013. The collected data originate from the Malczyce Hydrological Station on the 300th km of the Odra River. To assess the risk of flooding based on the collected data quarterly highs were selected. As a measure of flood risk, the authors suggested the probability of exceeding the emergency level in the studied section of the river. This risk was calculated using the theoretical distribution function of the quarterly heights of the water level. The study used the Gumbel distribution. A special attention was paid to the possibility of using the presented solutions for an integrated flood risk management process in accordance with applicable national and European legislation.
Rocznik
Strony
127--140
Opis fizyczny
Bibliogr. 25 poz., tab., rys.
Twórcy
  • Wrocław University of Science and Technology, Department of Environmental Engineering, Plac Grunwaldzki 9, 50-377 Wrocław, Poland
  • Wrocław University of Economics, Department of Quantitative Methods in Economics, ul. Komandorska 118/120, 53-345 Wrocław, Poland
  • General Tadeusz Kościuszko Military University of Land Forces Academy, ul. Piotra Czajkowskiego 109, 51-147 Wrocław, Poland
Bibliografia
  • [1] Directive 2000/60/EC, EU Water Framework Directive, The Official Journal (OJ L 327), 22 December 2000.
  • [2] Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks, The Official Journal (OJ L 288), 06 November 2007.
  • [3] ZWOŹDZIAK J., Flood risk management plans, Przeg. Kom., 2015, 281 (2), 43 (in Polish).
  • [4] RAMM-SZATKIEWICZ K., Implementation of the Floods Directive in the European Union, Przeg. Kom., 2015, 281 (2), 44–48 (in Polish).
  • [5] Flood Risk Management Plan for the Oder River Basin, National Water Management Authority, 2015, Poland, http://www.powodz.gov.pl/pl/plans_search. Cited 20 April 2016.
  • [6] BAJDUR W.M., GAJDA P., Innovations in the aspect of sustainable socio-economic development, Polskie Towarzystwo Zarządzania Produkcją, 2017 (in Polish).
  • [7] JELONEK D., JĘDRZEJCZYK W., Management No. 26, Scientific Notebooks of the Częstochowa University of Technology, Częstochowa 2017 (in Polish).
  • [8] JELONEK D., Selected problems of knowledge management and intellectual capital in the organization, Publishing Department of the Faculty of Management at Częstochowa University of Technology, Częstochowa 2012 (in Polish).
  • [9] Water Low of July 18, 2001, Polish Journal of Laws, No. 115, Item 1229.
  • [10] Act of 3 October 2008 on the Provision of Information on the Environment and its Protection, Public Participation in Environmental Protection and Environmental Impact Assessments, Polish Official Journal of the Laws, No. 199, Item 1227.
  • [11] DOGAN A., HAKTANIR T., SECKIN S., YURTAL R., Comparison of propability weighted moments and maximum likehood methods used in frequency analysis for Ceyhan River basin, Arab. J Sci. Eng., 2010, 35 (1B), 49–69.
  • [12] NACHABE M., PAYNTER S., Use of generalized extreme value covariates to improve estimation of trends and return frequencies for lake levels, J. Hydroinf., 2011, 13, 13–24.
  • [13] THOMAS M., REISS R., Statistical Analysis of Extreme Value with Applications to Insurance, Finance, Hydrology and Other Fields, Birkhauser, Berlin 2007.
  • [14] ENGELAND K., FRIGESSI A., HISDAL H., Practical extreme value modelling of hydrological floods and droughts. A case study, Extremes, 2004, 7 (1), 5–30.
  • [15] YuE S., BOBE B., LEGENDRE P., BRUNEAU P., The Gumbel mixed model for flood frequency analysis, J. Hydrol., 1999, 226, 88–100.
  • [16] Interagency Advisory Committee on Water Data, Guidelines for determining flood flow frequencies, Hydrology Subcommittee Bull., 1982, 17b.
  • [17] LEADBETTER M., LINDGREN G., ROOTZEN H., Extremes and related properties of random sequences and processes., Springer-Verlag, New York, 1983.
  • [18] KOTZ S., NADARAJAH S., Extreme value distributions. Theory and Applications, Imperial College Press, London 2005.
  • [19] SMITH R., Maximum likelihood estimation in a class of nonregular cases, Biometrika, 1985, 72, 69–90.
  • [20] BAJKIEWICZ-GRABOWSKA E., MIKULSKI Z., General hydrology, PWN, Warszawa 2011.
  • [21] KUŹMIŃSKI Ł., The applications of the kernel densities to the modeling the generalized Pareto distributions, Ekonometria, 2013, 41 (3), 55–64.
  • [22] PERICCHI L., RODRIGUEZ-ITURBE I., On statistical analysis of floods, [In:] A.C. Atkinson, S.E. Fienberg (Eds.), A Celebration in Statistics, The ISI Centenary Volume, Springer-Verlag, New York 1985, 511–541.
  • [23] KIEŁTYKA L., The use of expert systems in knowledge management, Wydawnictwo Politechniki Łódzkiej, Łódź, 2013, 53, 119–130 (in Polish).
  • [24] TODOROVIC P., A probabilistic approach to analysis and prediction of floods, Proc. 43rd Session ISI, Buenos Aires 1979.
  • [25] ZWOŹDZIAK J., Methods of forecasting and analysis of concentrations of air pollutants in the Black Triangle Region, Oficyna Wydawniczas Politechniki Wrocławskiej, Wroclaw 1995 (in Polish).
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-699eb70a-5b4a-4f2c-bf4b-818da3994a7d
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