Maximum daily rainfall analysis at selected meteorological stations in the upper Lusatian Neisse River basin

Abstract

Abstract. The scope of this study was to assess the usefulness of top probability distributions to describe maximum rainfall data in the Lusatian Neisse River basin, based on eight IMWM-NRI meteorological stations. The research material was composed of 50-year precipitation series of daily totals from 1961 to 2010. Misssing measurement data were estimated using a weighted average method. Homogeneity for refilled data were investigated by precipitation double aggregation curve. Correlation between the measurement data varied from 96 to 99% and did not indicate a violation of the homogeneity of rainfall data series. Variability of recorded daily precipitation maxima were studied by linear regression and non-parametric Mann-Kendall tests. Long-term period changes at maximum rainfalls for four stations remained statistically insignificant, and for the other four were significant, although the structure of maximums was relatively similar. To describe the measured data, there were used the Fréchet, Gamma, Generalized Exponential Distribution (GED), Gumbel, Log-normal and Weibull distributions. Particular distribution parameters were estimated using the maximum likelihood method. The conformity of the analyzed theoretical distributions with measured data was inspected using the Schwarz Bayesian information criterion (BIC) and also by the relative residual mean square error (RRMSE). Among others, the Gamma, GED, and Weibull distributions fulfilled the compliance criterion for each meteorological station respectively. The BIC criterion indicated GED as the best; however differences were minor between GED on the one hand and the Gamma and Weibull distributions on the other. After conducting the RRMSE analysis it was found that, in comparison to the other distributions, GED best describes the measured maximum rainfall data.

River Flow Prediction for Future Climate Using Long Series of Multi-Site Synthetic Data and MIKE SHE Model

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Criteria for identifying maximum rainfall determined by the peaks-over-threshold (POT) method under the Polish Atlas of Rainfall Intensities (PANDa) project

“…Such an approach allows us to obtain a larger statistical sample, for which it is necessary to define a threshold value that determines whether a particular rainfall event can be classified as an extreme event (Dupuis 1998). This approach is recommended by many authors (Lang et al 1999;Re, Barros 2009;Tramblay et al 2013;Bezak et al 2014;Wdowikowski et al 2016;Gharib et al 2017) and by the Intergovernmental Panel on Climate Change (IPCC 2014), among others. A detailed description of the POT method can be found in the papers by Coles (2001), andBommier (2014).…”

Municipality’s financial potencial and policy of flood risk management in Poland

“…Every year the phenomenon of flood causes huge losses around the world, both in lives and health of people, as well as the material losses [2]. In Poland last big floods were in 1997 and 2010 [3,4]. The predicted climate changes assume the increase of the frequency and strength of the occurrence of the meteorological-hydrological phenomena, including floods [2,4,5].…”

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