- Tytuł:
- Probability Function Estimation for the Maximum Precipitation Model Using Kernel Estimators
- Autorzy:
-
Karczewski, Maciej
Kaźmierczak, Bartosz
Michalski, Andrzej
Kuchar, Leszek - Powiązania:
- https://bibliotekanauki.pl/articles/2174916.pdf
- Data publikacji:
- 2022
- Wydawca:
- Politechnika Koszalińska. Wydawnictwo Uczelniane
- Tematy:
-
maximum precipitation
kernel estimation
hydrology - Opis:
- 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.
- Źródło:
-
Rocznik Ochrona Środowiska; 2022, 24; 260--275
1506-218X - Pojawia się w:
- Rocznik Ochrona Środowiska
- Dostawca treści:
- Biblioteka Nauki
Artykuł