Probability Function Estimation for the Maximum Precipitation Model Using Kernel Estimators

• Autorzy: Karczewski Maciej , Kaźmierczak Bartosz , Michalski Andrzej , Kuchar Leszek

Identyfikatory

DOI

10.54740/ros.2022.019

• Języki publikacji: EN

Abstrakty

EN

The distribution of maximum rainfall level is not a homogeneous phenomenon and is often characterised by multimodality and often the phenomenon of the heavy right-hand tail. Modelling this phenomenon using classic probability distributions leads to ignoring multimodality, thus underestimating or overestimating the predicted values in the tail tails – the most important from the point of view of safe dimensioning of drainage systems. To avoid the difficulties mentioned above, a non-parametric kernel estimator method of maximum precipitation density function was used (in the example of rainfall data from a selected station in Poland). The methodology proposed in the paper (for use on any rainfall data from other meteorological stations) will allow the development of more reliable local models of maximum precipitation.

Słowa kluczowe

EN

maximum precipitation; kernel estimation; hydrology

• Wydawca: Politechnika Koszalińska
• Czasopismo: Rocznik Ochrona Środowiska
• Rocznik: 2022
• Tom: Tom 24
• Strony: 260--275
• Opis fizyczny: Bibliogr. 38 poz., rys., tab.

Twórcy

autor

Karczewski Maciej

• Department of Mathematics, Faculty of Environmental Engineering and Geodesy, Wroclaw University of Environmental and Life Sciences, Poland

• https://orcid.org/0000-0001-8811-8916

autor

Kaźmierczak Bartosz

• Department of Water Supply and Sewerage Systems, Faculty of Environmental Engineering, Wroclaw University of Science and Technology, Poland

• https://orcid.org/0000-0003-4933-8451

autor

Michalski Andrzej

• Department of Mathematics, Faculty of Environmental Engineering and Geodesy, Wroclaw University of Environmental and Life Sciences, Poland

• https://orcid.org/0000-0001-9705-9276

autor

Kuchar Leszek

• Department of Mathematics, Faculty of Environmental Engineering and Geodesy, Wroclaw University of Environmental and Life Sciences, Poland

• https://orcid.org/0000-0002-4157-0910

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).