PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
Tytuł artykułu

Comparison of Two Nonstationary Flood Frequency Analysis Methods within the Context of the Variable Regime in the Representative Polish Rivers

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Changes in river flow regime resulted in a surge in the number of methods of non-stationary flood frequency analysis. Common assumption is the time-invariant distribution function with time-dependent location and scale parameters while the shape parameters are time-invariant. Here, instead of location and scale parameters of the distribution, the mean and standard deviation are used. We analyse the accuracy of the two methods in respect to estimation of time-dependent first two moments, time-invariant skewness and time-dependent upper quantiles. The method of maximum likelihood (ML) with time covariate is confronted with the Two Stage (TS) one (combining Weighted Least Squares and L-moments techniques). Comparison is made by Monte Carlo simulations. Assuming parent distribution which ensures the asymptotic superiority of ML method, the Generalized Extreme Value distribution with various values of linearly changing in time first two moments, constant skewness, and various time-series lengths are considered. Analysis of results indicates the superiority of TS methods in all analyzed aspects. Moreover, the estimates from TS method are more resistant to probability distribution choice, as demonstrated by Polish rivers’ case studies.
Czasopismo
Rocznik
Strony
206--236
Opis fizyczny
Bibliogr. 42 poz.
Twórcy
  • Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland
autor
  • Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland
  • Project CHIHE, Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland
  • Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland
autor
  • Warsaw University of Technology, Department of Civil Engineering in Płock, Płock, Poland
Bibliografia
  • Akaike, H. (1974), A new look at the statistical model identification, IEEE Trans. Automatic Control. 19, 6, 716-723, DOI: 10.1109/TAC.1974.1100705.
  • Clarke, R.T. (2002a), Fitting and testing the significance of linear trends in Gumbeldistributed data, Hydrol. Earth Syst. Sci. 6, 1, 17-24, DOI: 10.5194/hess-6- 17-2002.
  • Clarke, R.T. (2002b), Estimating time trends in Gumbel-distributed data by means of generalized linear models, Water Resour. Res. 38, 7, 16-1–16-11, DOI: 10.1029/2001WR000917.
  • Davison, A.C., and R.L. Smith (1990), Models for exceedances over high thresholds, J. Roy. Statist. Soc. B 52, 3, 393-442.
  • Feluch, W. (1994), Selected Methods of Kernel Estimation of Probability Density Function and Regression in Hydrology, Prace Naukowe – Inżynieria Środowiska, Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa, 85 pp. (in Polish).
  • Hall, J., B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T.R. Kjeldsen, J. Kriaučiūnienė, Z.W. Kundzewicz, M. Lang, M.C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R.A.P. Perdigão, L. Plavcová, M. Rogger, J.L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione, and G. Blöschl (2014), Understanding flood regime changes in Europe: A state-of-the-art assessment, Hydrol. Earth Syst. Sci. 18, 7, 2735-2772, DOI: 10.5194/hess- 18-2735-2014.
  • Hattermann, F.F., Z.W. Kundzewicz, S. Huang, T. Vetter, F.-W. Gerstengarbe, and P. Werner (2013), Climatological drivers of changes in flood hazard in Germany, Acta Geophys. 61, 2, 463-477, DOI: 10.2478/s11600-012-0070-4.
  • Hosking, J.R.M. (1990), L-moments: analysis and estimation of distributions using linear combinations of order statistics, J. Roy. Statist. Soc. B 52, 1, 105-124.
  • Hosking, J.R.M., and J.R. Wallis (1997), Regional Frequency Analysis: An Approach Based on L-Moments, Cambridge University Press, Cambridge, 224 pp.
  • Hosking, J.R.M., J.R. Wallis, and E.F. Wood (1985), Estimation of the generalized extreme-value distribution by the method of probability-weighted moments, Technometrics 27, 3, 251-261, DOI: 10.1080/00401706.1985.10488049.
  • Hurvich, C.M., and C.-L. Tsai (1989), Regression and time series model selection in small samples, Biometrika 76, 2, 297-307, DOI: 10.1093/biomet/76.2.297.
  • Kendall, M.G. (1975), Rank Correlation Methods, 4th ed., Charles Griffin, London.
  • Kochanek, K., W.G. Strupczewski, and E. Bogdanowicz (2012), On seasonal approach to flood frequency modelling. Part II: Flood frequency analysis of Polish rivers, Hydrol. Process. 26, 5, 717-730, DOI: 10.1002/hyp.8178.
  • Kochanek, K., W.G. Strupczewski, E. Bogdanowicz, W. Feluch, and I. Markiewicz (2013), Application of a hybrid approach in nonstationary flood frequency analysis – a Polish perspective, Nat. Hazards Earth Syst. Sci. Discuss. 1, 5, 6001-6024, DOI: 10.5194/nhessd-1-6001-2013.
  • Kundzewicz, Z.W., S. Kanae, S.I. Seneviratne, J. Handmer, N. Nicholls, P. Peduzzi, R. Mechler, L.M. Bouwer, N. Arnell, K. Mach, R. Muir-Wood, G.R. Brakenridge, W. Kron, G. Benito, Y. Honda, K. Takahashi, and B. Sherstyukov (2014), Flood risk and climate change: global and regional perspectives, Hydrolog. Sci. J. 59, 1, 1-28, DOI: 10.1080/02626667.2013. 857411.
  • Machado, M.J., B.A. Botero, J. López, F. Francés, A. Díez-Herrero, and G. Benito (2015), Flood frequency analysis of historical flood data under stationary and non-stationary modelling, Hydrol. Earth Syst. Sci. Discuss. 12, 525- 568, DOI: 10.5194/hessd-12-525-2015.
  • Markiewicz, I., E. Bogdanowicz, and W.G. Strupczewski (2014), On the accuracy of stability of estimators of probable maximum flows. In: K. Banasik, L. Hejduk, and E. Kaznowska (eds.), Hydrologia w Inżynierii i Gospodarce Wodnej, Monografie KGW-PAN, Komitet Gospodarki Wodnej PAN, Warszawa, 81-93 (in Polish).
  • Matalas, N.C., and M.A. Benson (1968), Note on the standard error of the coefficient of skewness, Water Resour. Res. 4, 1, 204-205, DOI: 10.1029/ WR004i001p00204.
  • Milly, P.C.D., J. Betancourt, M. Falkenmark, R.M. Hirsch, Z.W. Kundzewicz, D.P. Lettenmaier, and R.J. Stouffer (2008), Stationarity is dead: Whither water management? Science 319, 5863, 573-574, DOI: 10.1126/science. 1151915.
  • Mitosek, H.T., W.G. Strupczewski, and V.P. Singh (2006), Three procedures for selection of annual flood peak distribution, J. Hydrology 323, 1-4, 57-73, DOI: 10.1016/j.jhydrol.2005.08.016.
  • Montanari, A., G. Young, H.H.G. Savenije, D. Hughes, T. Wagener, L.L. Ren, D. Koutsoyiannis, C. Cudennec, E. Toth, S. Grimaldi, G. Blöschl, M. Sivapalan, K. Beven, H. Gupta, M. Hipsey, B. Schaefli, B. Arheimer, E. Boegh, S.J. Schymanski, G. Di Baldassarre, B. Yu, P. Hubert, Y. Huang, A. Schumann, D.A. Post, V. Srinivasan, C. Harman, S. Thompson, M. Rogger, A. Viglione, H. McMillan, G. Characklis, Z. Pang, and V. Belyaev (2013), “Panta Rhei—Everything Flows”: Change in hydrology and society—The IAHS Scientific Decade 2013-2022, Hydrolog. Sci. J. 58, 6, 1256-1275, DOI: 10.1080/02626667.2013.809088.
  • Pettitt, A.N. (1979), A non-parametric approach to the change-point problem, J. Roy. Statist. Soc. C 28, 2, 126-135, DOI: 10.2307/2346729.
  • Rao, A.R., and K.H. Hamed (2000), Flood Frequency Analysis, CRC Press, Boca Raton, 350 pp.
  • Rigby, R.A., and D.M. Stasinopoulos (2005), Generalized additive models for location, scale and shape, J. Roy. Statist. Soc. C 54, 3, 507-554, DOI: 10.1111/ j.1467-9876.2005.00510.x.
  • Rosenblatt, M. (1956), Remarks on some nonparametric estimates of a density function, Ann. Math. Statist. 27, 3, 832-837, DOI: 10.1214/aoms/1177728190.
  • Strupczewski, W.G. (1999), A farewell to the ML method in flood frequency analysis. In: V.P. Singh, I.W. Seo, and J.H. Sonu (eds.), Hydrologic Modeling. Proceedings of WEESHE, Water Resources Publications, LLC, Highlands Ranch, 291-306.
  • Strupczewski, W.G., and W. Feluch (1997), System of identification of an optimum flood frequency model with time dependent parameters (IDT). In: N.B. Harmanciouglu, M.N. Alpaslan, S.D. Ozkul, and V.P. Singh (eds.), Integrated Approach to Environmental Data Management Systems, NATO ASI Series, Vol. 31, Kluwer Acad. Publ., 291-300, DOI: 10.1007/978-94- 011-5616-5_25.
  • Strupczewski, W.G., and W. Feluch (1998), Investigation of trend in annual peak flow series. Part I. Maximum likelihood estimation. In: Proc. 2nd Int. Conf. on Climate and Water – A 1998 Perspective, 17-20 August 1998, Espoo, Finland, Vol. 1, 241-250.
  • Strupczewski, W.G., and Z. Kaczmarek (1998), Investigation of trend in annual peak flow series. Part II. Weighted Least Squares estimation. In: Proc. 2nd Int. Conf. on Climate and Water – A 1998 Perspective, 17-20 August 1998, Espoo, Finland, Vol. 1, 251-263.
  • Strupczewski, W.G., and Z. Kaczmarek (2001), Non-stationary approach to at-site flood frequency modelling. Part II. Weighted least squares estimation, J. Hydrol. 248, 1-4, 143-151, DOI: 10.1016/S0022-1694(01)00398-5.
  • Strupczewski, W.G., and H.T. Mitosek (1991), How to deal with nonstationary time series in the hydrologic projects. In: IAHS Symposium “Mitteilungsblatt des Hydrographischen Dienstes in Osterreich”, No. 65/66, Vienna, Austria, 36-40.
  • Strupczewski, W.G., and H.T. Mitosek (1995), Some aspects of hydrological design under non-stationarity. In: Z. Kundzewicz (ed.), New Uncertainty Concepts in Hydrology and Water Resources, Cambridge Univ. Press, Cambridge, 39-44.
  • Strupczewski, W.G., and H.T. Mitosek (1998), Investigation of trend in annual peak flow series. Part III Flood analysis of Polish rivers. In: Proc. 2nd Int. Conf. on Climate and Water – A 1998 Perspective, 17-20 August 1998, Espoo, Finland, Vol. 1, 264-272.
  • Strupczewski, W.G., V.P. Singh, and W. Feluch (2001a), Non-stationary approach to at-site flood frequency modelling. Part I. Maximum likelihood estimation, J. Hydrol. 248, 1-4, 123-142, DOI: 10.1016/S0022-1694(01) 00397-3.
  • Strupczewski, W.G., V.P. Singh, and H.T. Mitosek (2001b), Non-stationary approach to at-site flood frequency modelling. Part III. Flood analysis of Polish rivers, J. Hydrol. 248, 1-4, 152-167, DOI: 10.1016/S0022-1694(01) 00399-7.
  • Strupczewski, W.G., V.P. Singh, and S. Weglarczyk (2002a), Asymptotic bias of estimation methods caused by the assumption of false probability distribution, J. Hydrol. 258, 1-4, 122-148, DOI: 10.1016/S0022-1694(01)00563-7.
  • Strupczewski, W.G., S. Węglarczyk, and V.P. Singh (2002b), Model error in flood frequency estimation, Acta Geophys. Pol. 50, 2, 279-319.
  • Strupczewski, W.G., H.T. Mitosek, K. Kochanek, V.P. Singh, S. Weglarczyk (2006), Probability of correct selection from lognormal and convective diffusion models based on the likelihood ratio, Stoch. Environ. Res. Risk Assess. 20, 3, 152-163, DOI: 10.1007/s00477-005-0030-5.
  • Strupczewski, W.G., K. Kochanek, E. Bogdanowicz, and I. Markiewicz (2012), On seasonal approach to flood frequency modelling. Part I: Two-component distribution revisited, Hydrol. Process. 26, 5, 705-716, DOI: 10.1002/hyp. 8179.
  • Vogel, R.M., A. Rosner, and P.H. Kirshen (2013), Brief Communication: Likelihood of societal preparedness for global change: trend detection, Nat. Hazards Earth Syst. Sci. 13, 7, 1773-1778, DOI: 10.5194/nhess-13-1773-2013.
  • Wallis, J.R., N.C. Matalas, and J.R. Slack (1974), Just a moment! Water Resour. Res. 10, 2, 211-219, DOI: 10.1029/WR010i002p00211.
  • Yevjevich, V., and J.T.B. Obeysekera (1984), Estimation of skewness of hydrologic variables, Water Resour. Res. 20, 7, 935-943, DOI: 10.1029/WR020i007 p00935.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-85198a3c-13ac-443d-a18f-81d921b83155
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.