Abstract
The probability of the occurrence belonging to heavy rainfalls that directly triggers the flood is estimated with the common assumption that the process by which it occurred is under stationary conditions. By accepting this threat as if it does not exist in our globe, which is faced with the reality of global warming and climate change, estimating the required design values in the construction of hydraulic structures with frequency analysis of the relevant data would cause the failure of the water-related structures. This study was carried out to come up with how the regional and site-based frequency distribution would change under non-stationary conditions. The L-moments algorithm, Monte Carlo Simulation technique, and the magnitude of the trend calculated by Innovative Trend Analysis (ITA) were involved in scrutinizing the impact of non-stationary conditions on frequency analysis of annual maximum daily rainfall data sets. By including the own time-dependent change (trend) of each data in synthetic data, synthetically produced rainfall data was intended to reflect the actual conditions effectively. The simulated data has increased the heterogeneity of the entire region compared to the observed data and led to considerable differences in regional and site-based quantile estimates, and this difference became a nonlinear increase, especially after the 90% probability level. Based on this study, by considering stations with longer and equal or nearly equal observation periods in alternative regions, the change of frequency distribution behaviour in non-stationary conditions can be scrutinized with different methodologies.
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Hinis, M.A., Yurekli, K. Changing Characteristics of Regional and Site-based Frequency Distribution Under the Non-Stationary Process. KSCE J Civ Eng 27, 442–453 (2023). https://doi.org/10.1007/s12205-022-0651-y
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DOI: https://doi.org/10.1007/s12205-022-0651-y