Laux, P.; Weber, E.; Feldmann, D.; Kunstmann, H. The Robustness of the Derived Design Life Levels of Heavy Precipitation Events in the Pre-Alpine Oberland Region of Southern Germany. Atmosphere2023, 14, 1384.
Laux, P.; Weber, E.; Feldmann, D.; Kunstmann, H. The Robustness of the Derived Design Life Levels of Heavy Precipitation Events in the Pre-Alpine Oberland Region of Southern Germany. Atmosphere 2023, 14, 1384.
Laux, P.; Weber, E.; Feldmann, D.; Kunstmann, H. The Robustness of the Derived Design Life Levels of Heavy Precipitation Events in the Pre-Alpine Oberland Region of Southern Germany. Atmosphere2023, 14, 1384.
Laux, P.; Weber, E.; Feldmann, D.; Kunstmann, H. The Robustness of the Derived Design Life Levels of Heavy Precipitation Events in the Pre-Alpine Oberland Region of Southern Germany. Atmosphere 2023, 14, 1384.
Abstract
Extreme value analysis (EVA) is well-established to derive hydrometeorological design values for infrastructure that has to withstand extreme events. Since there is evidence of increased extremes with higher hazard potential under climate change, alterations of EVA are introduced for which statistical properties are no longer assumed to be constant but vary over time. In this study, both stationary and non-stationary EVA models are used to derive design life levels (DLLs) of daily precipitation in the pre-alpine Oberland region of Southern Germany, an orographically complex region characterized by heavy precipitation events and climate change. As EVA is fraught with uncertainties, it is crucial to quantify its methodological impacts: two theoretical distributions (i.e., Generalized Extreme Value (GEV) and Generalized Pareto (GP) distribution), four different parameter estimation techniques, (i.e., Maximum Likelihood Estimation (MLE), L-moments, Generalized Maximum Likelihood Estimation (GMLE), and Bayesian estimation method) are compared. Discrepancies due to the parameter estimation methods may reach up to 45 % of the mean absolute value, while differences between stationary and non-stationary models are of the same magnitude (differences in design levels up to 40%). Despite the underlying large methodological uncertainties, there is a robust tendency for increased DLLs in the Oberland region towards the end of this century based on the (non-)stationary models.
Keywords
Extreme Value Analysis; Design Life Levels; heavy precipitation events; stationary and non-stationary approaches; Oberland
Subject
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
