Return levels of maximum daily rainfall totals in the basin of the Upper Lusatian Neisse River

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020699%3A_____%2F21%3AN0000057" target="_blank" >RIV/00020699:_____/21:N0000057 - isvavai.cz</a>

Result on the web

<a href="https://iahr2020.pl/wp-content/uploads/2021/02/Book-of-Abstracts-15-02-2021.pdf" target="_blank" >https://iahr2020.pl/wp-content/uploads/2021/02/Book-of-Abstracts-15-02-2021.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Return levels of maximum daily rainfall totals in the basin of the Upper Lusatian Neisse River

Original language description

The Lusatian Neisse belongs to one of the most important European rivers. Its basin crosses the borders of three countries. In August 2010, the basin experienced disastrous floods that drew attention to this area also of those outside the hydrological community. It seems that the drivers of extreme rainfall events may change here either due to the climate itself or due to anthropogenic influences. The objective of this study was the investigation of the performance of several approaches allowing the estimation of rainfall design storms. Their comparison was made based on daily precipitation series available from 18 rain-gauges located within the upper part of this transboundary basin and covering the period 1961-2010. Using the peaks-over-threshold method, data representing maxima were derived and then subjected to trend analysis to decide whether increases or decreases in frequency and magnitude of extreme rainfall events have occurred. Moreover, the measured data were described by commonly used probability distributions: Fréchet, Gumbel, Weibull, Generalized Extreme Value, Log-normal, Gamma distributions, Generalized Exponential distribution, and Generalized Pareto distribution. To the previous stationary ones, also the point process technique was added which combines the Generalized Pareto distribution with the Poisson distribution when capturing nonstationary behaviour. The best-fitting distribution then allowed us to estimate the design storms.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10501 - Hydrology

Project

<a href="/en/project/SS01020366" target="_blank" >SS01020366: Using remote sensing to assess negative impacts of rainstorms</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

6th IAHR Europe Congress Abstract Book

ISBN

978-83-66847-01-9

ISSN

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e-ISSN

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Number of pages

2

Pages from-to

523-524

Publisher name

International Association for Hydro-Environment Engineering and Research

Place of publication

Warsaw

Event location

Warsaw

Event date

Feb 15, 2021

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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