Recent trends in annual maximum flows within the Upper Vistula River catchment

• Autorzy: Całek Mateusz , Węglarczyk Stanisław

Identyfikatory

DOI

10.14597/INFRAECO.2019.2.1.003

• Języki publikacji: EN

Abstrakty

EN

All uninterrupted time series of annual maximum flows of size at least 30 recorded in the period 1951-2016 in the Upper Vistula River catchment, were taken into trend analysis. Each of the 138 time series ended not earlier than in 2012. To estimate the trend, the nonparametric Theil-Kendall linear regression method was used. After removing the trend, lag-1 Kendall rank autocorrelation coefficient was calculated and, if the coefficient was significant at 5% level, was used to correct the variance of the Kendall S statistic which otherwise remained unchanged. Finally, the variance-corrected Mann-Kendall trend test was used, detecting 22 significant (at 5% level) linear trends of which only two were the effect of autocorrelation. All 138 significant and non-significant trends showed certain areal clustering clearly visible on the map of the catchment, which suggested dividing the area into three parts according the direction of trend and/or the number of statistically significant trends. Generally, the trends in the southern of the Upper Vistula River catchment are increasing, the opposite is true for the northern part. This finding does not concern the north-west part of the catchment where both kinds of trends are observed, which may be explained by strong anthropogenic influence.

Słowa kluczowe

EN

annual maximum flow; Upper Vistula River; Kendall-Theil linear regression; autocorrelation; variance correction approach

• Wydawca: Stowarzyszenie Infrastruktura i Ekologia Terenów Wiejskich
• Czasopismo: Infrastruktura i Ekologia Terenów Wiejskich
• Rocznik: 2019
• Tom: nr II/1
• Strony: 25--37
• Opis fizyczny: Bibliogr. 25 poz., rys.

Twórcy

autor

Całek Mateusz

• Cracow University of Technology Faculty of Environmental Engineering ul. Warszawska 24 31-155 Kraków

autor

Węglarczyk Stanisław

• Cracow University of Technology Faculty of Environmental Engineering ul. Warszawska 24 31-155 Kraków

Bibliografia

• Abdi, H. (2007). Kendall rank correlation. In: Salkind, N.J. Encyclopedia of Measurement and Statistics. Thousand Oaks (CA): Sage.
• Brath, A., Castellarin, A., Montanari, A. (1999). Detecting non stationarity in extreme rainfall data observed in Northern Italy, in: Proceedings of EGS - Plinius Conference on Mediterranean Storms, Maratea, 219-231.
• Burn, D.H., Hag Elnur, M.A. (2002). Detection of hydrologic trends and variability. J. Hydrol. 255: 107-122.
• Burn, D. H., Whitfield, P.H. (2018). Changes in flood events inferred from centennial length streamflow data records, Advances in Water Resources 121: 333-349.
• Cebulska, M., Twardosz, R., Cichocki J. (2007). Zmiany rocznych sum opadów atmosferycznych w dorzeczu górnej Wisły w latach 1881-2030, [w:] K. Piotrowicz, R. Twardosz (red.), Wahania klimatu w różnych skalach przestrzennych i czasowych, Instytut Geografii i Gospodarki Przestrzennej UJ, Kraków, 383-390.
• Cebulska, M. (2015). Wieloletnia zmienność maksymalnych opadów dobowych w Kotlinie Orawsko-Nowotarskiej (1984-2013), Czasopismo Inżynierii Lądowej, Środowiska i Architektury, 62 (3/I): 49-60.
• Chełmicki, W. (1991). Położenie, podział i cechy dorzecza in: Dynowska I., Maciejewski M. (red.) Dorzecze górnej Wisły. PWN, vol. I, Warszawa-Kraków.
• Douglas, E.M., Vogel, R.M., Kroll, C.N. (2000). Trends in floods and low flows in the United States: impact of spatial correlation, Journal of Hydrology 240: 90-105.
• Dulias R. (2016) The Impact of Mining on the Landscape: A Study of the Upper Silesian Coal Basin in Poland, Environmental Science and Engineering, Springer, doi: 10.1007/978-3-319-29541-1.
• Hamed, K.H., Rao, A.R. (1998). A modified Mann-Kendall trend test for autocorrelated data. J. Hydrol. 204 (1-4): 182-196.
• Helsel D.R., Hirsch R.M (2002). Statistical Methods in Water Resources, U.S. Geological Survey, Techniques of Water-Resources Investigations Book 4, Chapter A3.
• Kendon E.J., Roberts N. M., Fowler H. J., Roberts M. J., Chan S. C., Senior C.A. (2014). Heavier summer downpours with climate change revealed by weather forecast resolution model, Nature Climate Change 4: 570-576. doi:10.1038/nclimate2258.
• Khaliq, M.N., Ouarda, T.B.M.J., Gachon, P. (2009). Identification of temporal trends in annual and seasonal low flows occurring in Canadian rivers: The effect of short – and long-term persistence, J. Hydrol. 369: 183-197.
• Matalas, N. C., Langbein, W. B. (1962), Information content of the mean, J. Geophys. Res. 67(9): 3441-3448.
• Meshram, S.G., Singh, V.P., Meshram, C. (2016). Long-term trend and variability of precipitation in Chhattisgarh State, India, Theor Appl Climatol. doi:10.1007/s00704-016-1804-z.
• Prosdocimi, I., Kjeldsen, T. R., Svensson, C. (2014). Non-stationarity in annual and seasonal series of peak flow and precipitation in the UK. Natural Hazards and Earth System Sciences 14: 1125-1144.
• Razavi, T., Switzman, H., Arain, A., Coulibaly, P. (2016). Regional climate change trends and uncertainty analysis using extreme indices: A case study of Hamilton, Canada, Climate Risk Management 13: 43-63.
• Sen, P.K. (1968). Estimates of the Regression Coefficient Based on Kendall’s Tau, Journal of the American Statistical Association 63 (324): 1379-1389.
• Svoboda, V., Hanel, M., Máca, P., Kyselý, J. (2016). Projected changes of rainfall event characteristics for the Czech Republic. Journal of Hydrology and Hydromechanics 64, doi: 10.1515/johh-2016-0036.
• Theil, H. (1950). A rank-invariant method of linear and polynomial regression analysis, Part I, In the Proceedings of the Royal Netherlands Academy of Sciences, 53: 386-392.
• Trenberth, K. E., Dai, A., Rasmussen, R. M. & Parsons, D. B. (2003). The changing character of precipitation, Bull. Am. Meteorol. Soc. 84: 1205-1217.
• Wrzesiński, D. (2009). Tendencje zmian przepływu rzek polski w drugiej połowie XX wieku. Badania Fizjograficzne Seria A – Geografia Fizyczna 60: 147-162.
• Yue, S., Pilon, P., Phinney, B., Cavadias, G. (2002). The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol Process. 16 (9): 1807-1829.
• Zetterqvist, L. (1991). Statistical estimation and interpretation of trends in water quality time series, Water Resources Research 27 (7): 1637-1648.
• Zhang, Q., Gu, X., Singh, V.P., Xiao, M., Xu, C-Y. (2014). Stationarity of annual flood peaks during 1951-2010 in the Pearl River basin, China. J. Hydrol. 519: 3263-3274.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).