Regionalisation of rainfall depth-duration-frequency curves with different data types in Germany

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • Bora Shehu
  • Winfried Willems
  • Henrike Stockel
  • Luisa Bianca Thiele
  • Uwe Haberlandt

Externe Organisationen

  • Universität Potsdam
  • Ingenieurhydrologie, Angewandte Wasserwirtschaft und Geoinformatik (IAWG)
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Details

OriginalspracheEnglisch
Seiten (von - bis)1109-1132
Seitenumfang24
FachzeitschriftHydrology and Earth System Sciences
Jahrgang27
Ausgabenummer5
PublikationsstatusVeröffentlicht - 14 März 2023

Abstract

Rainfall depth-duration-frequency (DDF) curves are required for the design of several water systems and protection works. For the reliable estimation of such curves, long and dense observation networks are necessary, which in practice is seldom the case. Usually observations with different accuracy, temporal resolution and density are present. In this study, we investigate the integration of different observation datasets under different methods for the local and regional estimation of DDF curves in Germany. For this purpose, two competitive DDF procedures for local estimation (Koutsoyiannis et al., 1998; Fischer and Schumann, 2018) and two for regional estimation (kriging theory vs. index based) are implemented and compared. Available station data from the German Weather Service (DWD) for Germany are employed, which includes 5000 daily stations with more than 10 years available, 1261 high-resolution (1 min) recordings with an observation period between 10 and 20 years, and finally 133 high-resolution (1 min) recordings with 60-70 years of observations. The performance of the selected approaches is evaluated by cross-validation, where the local DDFs from the long sub-hourly time series are considered the true reference. The results reveal that the best approach for the estimation of the DDF curves in Germany is by first deriving the local extreme value statistics based on Koutsoyiannis et al.'s (1998) framework and later using the kriging regionalisation of long sub-hourly time series with the short sub-hourly time series acting as an external drift. The integration of the daily stations proved to be useful only for DDF values of a low return period (T[a]<10 years) but does not introduce any improvement for higher return periods (T[a]≥10 years).

ASJC Scopus Sachgebiete

Zitieren

Regionalisation of rainfall depth-duration-frequency curves with different data types in Germany. / Shehu, Bora; Willems, Winfried; Stockel, Henrike et al.
in: Hydrology and Earth System Sciences, Jahrgang 27, Nr. 5, 14.03.2023, S. 1109-1132.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Shehu B, Willems W, Stockel H, Thiele LB, Haberlandt U. Regionalisation of rainfall depth-duration-frequency curves with different data types in Germany. Hydrology and Earth System Sciences. 2023 Mär 14;27(5):1109-1132. doi: 10.5194/hess-27-1109-2023
Shehu, Bora ; Willems, Winfried ; Stockel, Henrike et al. / Regionalisation of rainfall depth-duration-frequency curves with different data types in Germany. in: Hydrology and Earth System Sciences. 2023 ; Jahrgang 27, Nr. 5. S. 1109-1132.
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abstract = "Rainfall depth-duration-frequency (DDF) curves are required for the design of several water systems and protection works. For the reliable estimation of such curves, long and dense observation networks are necessary, which in practice is seldom the case. Usually observations with different accuracy, temporal resolution and density are present. In this study, we investigate the integration of different observation datasets under different methods for the local and regional estimation of DDF curves in Germany. For this purpose, two competitive DDF procedures for local estimation (Koutsoyiannis et al., 1998; Fischer and Schumann, 2018) and two for regional estimation (kriging theory vs. index based) are implemented and compared. Available station data from the German Weather Service (DWD) for Germany are employed, which includes 5000 daily stations with more than 10 years available, 1261 high-resolution (1 min) recordings with an observation period between 10 and 20 years, and finally 133 high-resolution (1 min) recordings with 60-70 years of observations. The performance of the selected approaches is evaluated by cross-validation, where the local DDFs from the long sub-hourly time series are considered the true reference. The results reveal that the best approach for the estimation of the DDF curves in Germany is by first deriving the local extreme value statistics based on Koutsoyiannis et al.'s (1998) framework and later using the kriging regionalisation of long sub-hourly time series with the short sub-hourly time series acting as an external drift. The integration of the daily stations proved to be useful only for DDF values of a low return period (T[a]<10 years) but does not introduce any improvement for higher return periods (T[a]≥10 years).",
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Download

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T1 - Regionalisation of rainfall depth-duration-frequency curves with different data types in Germany

AU - Shehu, Bora

AU - Willems, Winfried

AU - Stockel, Henrike

AU - Thiele, Luisa Bianca

AU - Haberlandt, Uwe

N1 - Funding Information: The results presented in this study are part of the research project “Investigating Different Methods for Revising and Updating the Heavy Rainfall Statistics in Germany (MUNSTAR)”, funded by the German Ministry of Agriculture and Environment Mecklenburg-Vorpommern and the Federal State Funding Programme “Water, Soil and Waste”, who are gratefully acknowledged. We are also thankful for the provision and right to use the data from the German National Weather Service (Deutscher Wetterdienst DWD), more specifically Thomas Deutschländer and Thomas Junghänel. Lastly, we would like to thank Paweł Licznar and Juraj Parajka for their comments that improved the final version of the paper.

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N2 - Rainfall depth-duration-frequency (DDF) curves are required for the design of several water systems and protection works. For the reliable estimation of such curves, long and dense observation networks are necessary, which in practice is seldom the case. Usually observations with different accuracy, temporal resolution and density are present. In this study, we investigate the integration of different observation datasets under different methods for the local and regional estimation of DDF curves in Germany. For this purpose, two competitive DDF procedures for local estimation (Koutsoyiannis et al., 1998; Fischer and Schumann, 2018) and two for regional estimation (kriging theory vs. index based) are implemented and compared. Available station data from the German Weather Service (DWD) for Germany are employed, which includes 5000 daily stations with more than 10 years available, 1261 high-resolution (1 min) recordings with an observation period between 10 and 20 years, and finally 133 high-resolution (1 min) recordings with 60-70 years of observations. The performance of the selected approaches is evaluated by cross-validation, where the local DDFs from the long sub-hourly time series are considered the true reference. The results reveal that the best approach for the estimation of the DDF curves in Germany is by first deriving the local extreme value statistics based on Koutsoyiannis et al.'s (1998) framework and later using the kriging regionalisation of long sub-hourly time series with the short sub-hourly time series acting as an external drift. The integration of the daily stations proved to be useful only for DDF values of a low return period (T[a]<10 years) but does not introduce any improvement for higher return periods (T[a]≥10 years).

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