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

100%

Wdowikowski M. , Kazmierczak B. , Ledvinka O.

Meteorology Hydrology and Water Management. Research and Operational Applications

2016

tom 04

nr 1

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.

Estimating the runoff coefficient using the analytic hierarchy process

67%

Lallam F. , Megnounif A. , Ghenim A. N.

Journal of Water and Land Development

2018

tom no. 38

67--74

The runoff coefficient (RC) is a parameter that is very often used in surface hydrology in order to characterize the drainage capacity of a watershed. The traditional estimate of this coefficient is often made from abacuses based on 2 or 3 parameters to the maximum. In this work, three numerical models are presented. Two models are based on experimental work. The first one is based on three criteria, namely the vegetation cover, the type of soil, and the slope. The second one considers the size of the watershed, the maximum daily rainfall and the type of soil. In practice, it is not easy to estimate the coefficient of runoff by simultaneously considering the influence of several criteria. In order to overcome this problem, a third model is developed and presented; it allows capitalizing the information from the first two models mentioned above. The objective of the present work is to be able to verify the comparability of these criteria and to assess the relative importance of each of them.

Współczynnik odpływu (RC) jest parametrem często używanym w hydrologii wód powierzchniowych w celu charakterystyki zdolności drenarskiej zlewni. Tradycyjnie ocenę tego współczynnika wykonuje się za pomocą obliczeń bazujących maksymalnie na 2–3 parametrach. W niniejszej pracy przedstawiono trzy modele numeryczne. Dwa z nich oparte są na badaniach eksperymentalnych. Pierwszy bazuje na trzech kryteriach: pokrycie roślinnością, typ gleby i nachylenie terenu. Drugi uwzględnia rozmiar zlewni, maksymalny opad dobowy i typ gleby. W praktyce nie jest łatwo ocenić współczynnik odpływu przez uwzględnienie wpływu kilku kryteriów równocześnie. Aby rozwiązać ten problem, zbudowano i przedstawiono trzeci model. Umożliwia on połączenie informacji z dwóch wyżej wymienionych modeli. Celem pracy jest umożliwienie weryfikacji porównywalności kryteriów i dokonanie oceny względnego znaczenia każdego z nich.