Abstract

The aim of this study was to determine the best probability distributions for calculating the maximum annual daily precipitation with the specific probability of exceedance (Pmaxp%). The novelty of this study lies in using the peak-weighted root mean square error (PWRMSE), the root mean square error (RMSE), and the coefficient of determination (R2) for assessing the fit of empirical and theoretical distributions. The input data included maximum daily precipitation records collected in the years 1971–2014 at 51 rainfall stations from the Upper Vistula Basin, Southern Poland. The value of Pmaxp% was determined based on the following probability distributions of random variables: Pearson’s type III (PIII), Weibull’s (W), log-normal, generalized extreme value (GEV), and Gumbel’s (G). Our outcomes showed a lack of significant trends in the observation series of the investigated random variables for a majority of the rainfall stations in the Upper Vistula Basin. We found that the peak-weighted root mean square error (PWRMSE) method, a commonly used metric for quality assessment of rainfall-runoff models, is useful for identifying the statistical distributions of the best fit. In fact, our findings demonstrated the consistency of this approach with the RMSE goodness-of-fit metrics. We also identified the GEV distribution as recommended for calculating the maximum daily precipitation with the specific probability of exceedance in the catchments of the Upper Vistula Basin.

Highlights

  • The analysis of the maximum annual daily precipitation (Pmax ) is one of the crucial factors for the management of water resources in a catchment [1]

  • Our calculations showed a lack of significant trends in the observation series of the investigated random variables for a majority of rainfall stations in the Upper Vistula Basin (44 out of 51)

  • The multimodality of the empirical density function for the rainfall stations with significant trends confirmed the change in meteorological mechanisms in the surveyed multi-year period that affected the maximum daily precipitation in the Upper Vistula Basin

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Summary

Introduction

The analysis of the maximum annual daily precipitation (Pmax ) is one of the crucial factors for the management of water resources in a catchment [1]. Determining the maximum annual daily precipitation with a specific probability of exceedance (Pmaxp% ) is necessary to tackle the issues of excessive or deficient precipitation and, to meet regional water needs. Based on a sufficiently long observation series of the maximum annual daily precipitation, it is possible to predict Pmaxp% by using probability distributions of random variables. Pmaxp% is commonly determined by using the following probability distribution functions: normal distribution, log-normal distribution, Pearson’s type III, exponential function, Gumbel’s distribution, generalized extreme value distribution (GEV), and Weibull’s and Pareto’s distributions [7,8,9,10,11,12,13]. The selection of an inappropriate function for a region may result in underestimating or overestimating the maximum hydro-meteorological events with a specific probability of exceedance [17]

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