Published July 26, 2022 | Version 1.0

Regional Flood Frequency Analysis of the Sava River in South-Eastern Europe

  • 1. Department of Geography, Tourism and Hotel Management, Faculty of Sciences, University of Novi Sad, Trg Dositeja Obradovića 3, 21000 Novi Sad , Serbia
  • 2. Faculty of Civil and Geodetic Engineering, University of Ljubljana, Jamova cesta 2, 1000 Ljubljana , Slovenia
  • 3. Climate Risk Analysis, Kreuzstrasse 27, 37581 Bad Gandersheim, Germany

Description

Journal: Sustainability

Abstract: Regional flood frequency analysis (RFFA) is a powerful method for interrogating hydrological series since it combines observational time series from several sites within a region to estimate risk-relevant statistical parameters with higher accuracy than from single-site series. Since RFFA extreme value estimates depend on the shape of the selected distribution of the data-generating stochastic process, there is need for a suitable goodness-of-distributional-fit measure in order to optimally utilize given data. Here we present a novel, least-squares-based measure to select the optimal fit from a set of five distributions, namely Generalized Extreme Value (GEV), Generalized Logistic, Gumbel, Log-Normal Type III and Log-Pearson Type III. The fit metric is applied to annual maximum discharge series from six hydrological stations along the Sava River in South-eastern Europe, spanning the years 1961 to 2020. Results reveal that (1) the Sava River basin can be assessed as hydrologically homogeneous and (2) the GEV distribution provides typically the best fit. We offer hydrological‒meteorological insights into the differences among the six stations. For the period studied, almost all stations exhibit statistically insignificant trends, which renders the conclusions about flood risk as relevant for hydrological sciences and the design of regional flood protection infrastructure.

URL: https://www.mdpi.com/2071-1050/14/15/9282

The uploaded datasets are the Annual Maximum Series of Sava River runoff for the six analysed hydrological stations: Radovljica, Čatež, Zagreb, Jasenovac, Županja and S. Mitrovica.

Notes

This research was supported by ExtremeClimTwin project, which has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 952384.

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Additional details

Funding

European Commission
EXtremeClimTwin - Twinning for the advancement of data-driven multidisciplinary research into hydro-climatic extremes to support risk assessment and decision making 952384