Characterisation of the floods in the Danube River basin through flood frequency and seasonality analysis
Analiza značilnosti poplav v povodju reke Donave s pomočjo verjetnostne analize in analize sezonskosti
- Avtorji: Martin Morlot, Mitja Brilly, Mojca Šraj
- Citat: Acta hydrotechnica, vol. 32, no. 57, pp. 73-89, 2019. https://doi.org/10.15292/acta.hydro.2019.06
- Povzetek: Poplave so ena izmed naravnih nesreč, ki povzročajo veliko gospodarsko škodo in zato močno vplivajo na družbo. Razumevanje prostorskih in časovnih značilnosti poplav je eden od ključnih dejavnikov učinkovitega upravljanja voda. Povodje reke Donave je pomembna regija v Evropi, poplave v povodju pa se pojavljajo že skozi celo zgodovino. V raziskavi smo izdelali celovito analizo poplav v povodju reke Donave, in sicer verjetnostne analize visokih vod in analize sezonskosti na podlagi maksimalnih letnih pretokov s 87 vodomernih postaj. Rezultati verjetnostnih analiz kažejo opazno grupiranje vodomernih postaj glede na najustreznejšo porazdelitveno funkcijo. Kot najustreznejši porazdelitveni funkciji za analize visokih vod na vodomernih postajah v povodju reke Donave sta se izkazali generalizirana porazdelitev ekstremnih vrednosti (GEV) in logaritemska Pearsonova 3 porazdelitev (LP3). Izmed 86 obravnavanih vodomernih postaj je bila kar za 76 postaj ena od omenjenih dveh funkcij med prvima dvema najustreznejšima. Analiza sezonskosti je pokazala, da se velike poplave v povodju reke Donave pojavljajo večinoma spomladi, sezonskost pojavljanja poplav pa je močno regijsko pogojena.
- Ključne besede: povodje Donave, poplave, verjetnostna analiza visokih vod, sezonskost
- Polno besedilo: a32mmo.pdf
- Viri:
- ASCE. (1953). Report of the subcommittee on the joint division committee on floods. Am. Soc. Civil Engineers Trans., v. 118, 1220–1230.
- Asquith, W.H. (2018). lmomco—L-moments, censored L-moments, trimmed L-moments, L-comoments, and many distributions (Version R package 2.3.2). Texas Tech University, Lubbock, Texas. Available at: https://CRAN.R-project.org/package=lmomco (accessed 5 February 2018)
- Bačová-Mitková, Onderka, M. (2010). Analysis of extreme hydrological events on the Danube using the peak over threshold method. Journal of Hydrology and Hydromechanics, 58(2), 88–101. https://doi.org/10.2478/v10098-010-0009-x
- Bačová-Mitková, V., Halmová, D. (2014). Joint modeling of flood peak discharges, volume and duration: a case study of the Danube River in Bratislava. Journal of Hydrology and Hydromechanics, 62, 3, 186–196. https://doi.org/10.2478/johh-2014-0026.
- Barbalič D., Petraš J. (2012). Seasonal occurrence of maximum annual flows in the Danube River basin in Croatia. Građevinar, 64(1), 33–38. https://doi.org/10.14256/JCE.628.2011
- Bayliss, A. C. and Jones, R. C. (1993). Peaks-over-threshold flood database: Summary statistics and seasonality. IH Report No. 121, Institute of Hydrology, Wallingford, UK, 61 p.
- Bezak, N., Brilly, M., Šraj, M. (2014). Comparison between the peaks-over-threshold method and the annual maximum method for flood frequency analysis. Hydrological Sciences Journal, 59(5), 959–977. https://doi.org/10.1080/02626667.2013.831174
- Bezak, N., Brilly, M., Šraj, M. (2016). Flood frequency analyses, statistical trends and seasonality analyses of discharge data: A case study of the Litija station on the Sava River. Journal of Flood Risk Management, 9(2), 154–168. https://doi.org/10.1111/jfr3.12118
- Bezak, N., Mikoš, M. (2014). Estimation of design floods using univariate and multivariate flood frequency approach with regard to one wet year. Acta Hydrotechnica, 27(47), 103–117.
- Blöschl, G., Hall, J., Viglione, A., Perdigão, R. A. P., Parajka, J., Merz, B., […], Živković, N. (2017). Changing climate shifts timing of European floods. Science, 357, 588–509. https://doi.org/10.1126/science.aan2506
- Blöschl, G., Hall, J., Viglione, A., Perdigão, R. A. P., Parajka, J., Merz, B., […], Živković, N. (2019). Changing climate both increases and decreases European river floods. Nature, 573(7772), 108–111. https://doi.org/10.1038/s41586-019-1495-6
- Burn, D. H. (1997). Catchment similarity for regional flood frequency analysis using seasonality measures. Journal of Hydrology, 202(1), 212–230. https://doi.org/10.1016/S0022-1694(97)00068-1
- Chowdhury, J. U., Stedinger, J. R., Lu, L.-H. (1991). Goodness-of-fit tests for regional generalized extreme value flood distributions. Water Resources Research, 27(7), 1765–1776. https://doi.org/10.1029/91WR00077
- England Jr., J. F., Cohn, T. A., Faber, B. A., Stedinger, J. R., Thomas Jr., W. O., Veilleux, A. G., […], Mason Jr., R. R. (2018). Guidelines for determining flood flow frequency - Bulletin 17C (USGS Numbered Series No. 4-B5), Reston, VA, U.S., Geological Survey, 168 p. Available at: http://pubs.er.usgs.gov/publication/tm4B5 (accessed 25 January 2018)
- Grimaldi, S., Kao, S.-C., Castellarin, A., Papalexiou, S.-M., Viglione, A., Laio, F., … Gedikli, A. (2011). 2.18 - Statistical Hydrology. In P. Wilderer (Ed.), Treatise on Water Science, 479–517. https://doi.org/10.1016/B978-0-444-53199-5.00046-4
- Gu, Z., Gu, L., Eils, R., Schlesner, M., Brors, B. (2014). Circlize implements and enhances circular visualization in R. Bioinformatics, 30(19), 2811–2812.
- Hall, J., Blöschl, G. (2017). Spatial Patterns and Characteristics of Flood Seasonality in Europe. Hydrology and Earth System Sciences Discussions, 1–28. https://doi.org/10.5194/hess-2017-649
- Hosking, J. R. M. (1990). L-Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics. Journal of the Royal Statistical Society. Series B (Methodological), 52(1), 105–124.
- Hosking, J.R.M. and Wallis, J.R. (2005). Regional frequency analysis: an approach based on L-moments. Cambridge University Press.
- Iacobellis, V., Fiorentino, M., Gioia, A., Manfreda, S. (2010). Best Fit and Selection of Theoretical Flood Frequency Distributions Based on Different Runoff Generation Mechanisms. Water, 2(2), 239–256. https://doi.org/10.3390/w2020239
- ICPDR. (2011). Danube Basin: Facts and Figures Brochure. Available at: http://www.icpdr.org/main/danube-basin-facts-and-figures-brochure (accessed 20 June 2018)
- Jarvis, C. S. (1936). Floods in the United States: Magnitude and frequency. USGS Numbered Series, U.S. Government Printing Office, 500 p. Available at: http://pubs.er.usgs.gov/publication/wsp771 (accessed 6 March 2018)
- Jones, W. (Ed.). (2007). Life and Europe’s rivers: Protecting and improving our water resources. Luxembourg: Office for Official Publications of the European Communities.
- Kidson, R., Richards, K. S. (2005). Flood frequency analysis: Assumptions and alternatives. Progress in Physical Geography: Earth and Environment, 29(3), 392–410. https://doi.org/10.1191/0309133305pp454ra
- Kobierska, F., Engeland, K., Thorarinsdottir, T. (2018). Evaluation of design flood estimates – a case study for Norway. Hydrology Research, 49(2), 450–465. https://doi.org/10.2166/nh.2017.068
- Kochanek, K., Renard, B., Arnaud, P., Aubert, Y., Lang, M., Cipriani, T., Sauquet, E. (2014). A data-based comparison of flood frequency analysis methods used in France. Nat. Hazards Earth Syst. Sci., 14(2), 295–308. https://doi.org/10.5194/nhess-14-295-2014
- Lin, B., Vogel, J. L. (1993). A Comparison of L-Moments with Method of Moments. 443–448. Available at: http://cedb.asce.org/CEDBsearch/record.jsp?dockey=0083395 (accessed 10 April 2018)
- Mahdi, S., Cenac, M. (2005). Estimating Parameters of Gumbel Distribution using the Methods of Moments, probability weighted Moments and maximum likelihood. Revista de Matemática: Teoría y Aplicaciones, 12(1–2), 151–156.
- Mitková, V. B., Onderka, M. (2010). Analysis of extreme hydrological Events on the Danube using the Peak Over Threshold method. Journal of Hydrology and Hydromechanics, 58(2), 88–101. https://doi.org/10.2478/v10098-010-0009-x
- Morlot, M. (2018). Characterisation of the floods in the Danube River basin through univariate and multivariate (copula functions) flood frequency analysis, seasonality and regionalisation. Unpublished Master thesis, Master Program in Flood Risk Management. IHE Delft and University of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana, 75 p.
- Ninov, P., Brilly, M. (Eds.). (2017). Danube conference 2017 electronic book with full papers from XXVII Conference of the Danubian Countries on Hydrological Forecasting and Hydrological Bases of Water Management. Sofia.
- NIST/SEMATECH. (2010). NIST/SEMATECH e-Handbook of Statistical Methods. Available at: http://www.itl.nist.gov/div898/handbook/ (accessed 2 April 2018)
- Parajka J., Kohnova S., Merz R., Szolgay J., Hlavcova K., Blöschl G. (2009). Comparative analysis of the seasonality of hydrological characteristics in Slovakia and Austria. Hydrological Sciences Journal, 54(3), 456–473. https://doi.org/10.1623/hysj.54.3.456
- Parajka J., Kohnova S., Balint G., Barbuc M., Borga M., Claps P., Cheval S., Dumitrescu A., Gaume E., Hlavcˇova K., Merz R., Pfaundler M., Stancalie G., Szolgay J., Blöschl G. (2010). Seasonal characteristics of flood regimes across the Alpine-Carpathian range. Journal of Hydrology, 394(1–2), 78–89. https://doi.org/10.1016/j.jhydrol.2010.05.015
- Poduje, A. C. C., Belli, A., Haberlandt, U. (2014). Dam risk assessment based on univariate versus bivariate statistical approaches: A case study for Argentina. Hydrological Sciences Journal, 59(12), 2216–2232. https://doi.org/10.1080/02626667.2013.871014
- R Core Team. (2018). R: A language and environment for statistical computing. R Foundation for statistical computing, Vienna, Austria. Available at: https://www.R-project.org/ (accessed 1 February 2018)
- Robson, A., Reed, D. W. (1999). Flood estimation handbook. Vol. 3. Wallingford: Institute of Hydrology.
- Salas, J.D., et al. (2013). Quantifying the uncertainty of return period and risk in hydrologic design. Journal of Hydrologic Engineering, 18(5), 518–526. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000613
- Sankarasubramanian, A., Srinivasan, K. (1999). Investigation and comparison of sampling properties of L-moments and conventional moments. Journal of Hydrology, 218(1), 13–34. https://doi.org/10.1016/S0022-1694(99)00018-9
- Shahzad, M. N., Asghar, Z. (2013). Comparing TL-Moments, L-Moments and Conventional Moments of Dagum Distribution by Simulated data. Revista Colombiana de Estadística, 15.
- Stevenson, A. (Ed.). (2010). Oxford Dictionary of English. Available at: http://www.oxfordreference.com/view/10.1093/acref/9780199571123.001.0001/acref-9780199571123 (accessed 6 March 2018)
- Šimková, T., Picek, J. (2017). A comparison of L-, LQ-, TL-moment and maximum likelihood high quantile estimates of the GPD and GEV distribution. Communications in Statistics - Simulation and Computation, 46(8), 5991–6010. https://doi.org/10.1080/03610918.2016.1188206
- Šraj, M., Bezak, N., Brilly, M. (2012). The influence of the choice of method on the results of frequency analysis of peaks, volumes and durations of flood waves of the Sava River in Litija, Acta hydrotechnica, 25(42), 41–58. (In Slovenian).
- Šraj, M., Bezak, N., Brilly, M. (2015). Bivariate flood frequency analysis using the copula function: A case study of the Litija station on the Sava River. Hydrological Processes, 29(2), 225–238. https://doi.org/10.1002/hyp.10145
- Šraj, M., Petan, S., Kobold, M., Bezak, N., Brilly, M. (2019). Status quo of the Danube basin countriesʼ flood and ice forecasting systems and methodologies. In: European Geosciences Union, General Assembly 2019, Vienna, Austria, 7-12 April 2019, (Geophysical research abstracts, Vol. 21). München: European Geosciences Union. 2019.
- UNDP/GEF. (2010). Danube Regional Project: Morphology & climate. Available at: http://www.undp-drp.org/drp/danube_morphology_and_climate.html (accessed 12 July 2018)
- Vittal, H., Singh, J., Kumar, P., Karmakar, S. (2015). A framework for multivariate data-based at-site flood frequency analysis: Essentiality of the conjugal application of parametric and nonparametric approaches. Journal of Hydrology, 525, 658–675. https://doi.org/10.1016/j.jhydrol.2015.04.024
- WMO (World Meteorological Organization). (1989). Statistical distributions for flood frequency analysis. Geneva: World Meteorological Organization.
- Zambrano-Bigiarini, M. (2017a). HydroGOF: Goodness-of-fit functions for comparison of simulated and observed hydrological time series (Version 0.3-10, R package). Available at: https://doi.org/10.5281/zenodo.840087 (accessed 5 February 2018)
- Zambrano-Bigiarini, M. (2017b). hydroTSM: Time Series Management, Analysis and Interpolation for Hydrological Modelling (Version 0.5-1). Available at: https://CRAN.R-project.org/package=hydroTSM (accessed 5 February 2018)
- Zeng, X., Wang, D., Wu, J. (2015). Evaluating the Three Methods of Goodness of Fit Test for Frequency Analysis. Journal of Risk Analysis and Crisis Response, 5(3), 178. https://doi.org/10.2991/jrarc.2015.5.3.5