Articles | Volume 29, issue 16
https://doi.org/10.5194/hess-29-3917-2025
https://doi.org/10.5194/hess-29-3917-2025
Research article
 | 
25 Aug 2025
Research article |  | 25 Aug 2025

Estimation of radar-based area–depth–duration–frequency curves with special focus on spatial sampling problems

Golbarg Goshtasbpour and Uwe Haberlandt

Related authors

Flood frequency analysis using mean daily flows vs. instantaneous peak flows
Anne Bartens, Bora Shehu, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 28, 1687–1709, https://doi.org/10.5194/hess-28-1687-2024,https://doi.org/10.5194/hess-28-1687-2024, 2024
Short summary
A semi-parametric hourly space–time weather generator
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023,https://doi.org/10.5194/hess-27-3957-2023, 2023
Short summary
Uncertainty estimation of regionalised depth–duration–frequency curves in Germany
Bora Shehu and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 2075–2097, https://doi.org/10.5194/hess-27-2075-2023,https://doi.org/10.5194/hess-27-2075-2023, 2023
Short summary
Regionalisation of rainfall depth–duration–frequency curves with different data types in Germany
Bora Shehu, Winfried Willems, Henrike Stockel, Luisa-Bianca Thiele, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 1109–1132, https://doi.org/10.5194/hess-27-1109-2023,https://doi.org/10.5194/hess-27-1109-2023, 2023
Short summary
Comparison of rainfall generators with regionalisation for the estimation of rainfall erosivity at ungauged sites
Ross Pidoto, Nejc Bezak, Hannes Müller-Thomy, Bora Shehu, Ana Claudia Callau-Beyer, Katarina Zabret, and Uwe Haberlandt
Earth Surf. Dynam., 10, 851–863, https://doi.org/10.5194/esurf-10-851-2022,https://doi.org/10.5194/esurf-10-851-2022, 2022
Short summary

Cited articles

Bárdossy, A. and Pegram, G.: Intensity–duration–frequency curves exploiting neighbouring extreme precipitation data, Hydrolog. Sci. J., 63, 1593–1604, https://doi.org/10.1080/02626667.2018.1524987, 2018. a, b, c, d
Bennett, B., Lambert, M., Thyer, M., Bates, B. C., and Leonard, M.: Estimating Extreme Spatial Rainfall Intensities, J. Hydrol. Eng., 21, 04015074, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001316, 2016. a, b, c, d
Berndt, C., Rabiei, E., and Haberlandt, U.: Geostatistical merging of rain gauge and radar data for high temporal resolutions and various station density scenarios, J. Hydrol., 508, 88–101, https://doi.org/10.1016/j.jhydrol.2013.10.028, 2013. a
Bertini, C., Buonora, L., Ridolfi, E., Russo, F., and Napolitano, F.: On the Use of Satellite Rainfall Data to Design a Dam in an Ungauged Site, Water, 12, 3028, https://doi.org/10.3390/w12113028, 2020. a
Bezak, N., Šraj, M., and Mikoš, M.: Copula-based IDF curves and empirical rainfall thresholds for flash floods and rainfall-induced landslides, J. Hydrol., 541, 272–284, https://doi.org/10.1016/j.jhydrol.2016.02.058, 2016. a
Download
Short summary
A method for estimating extreme rainfall from radar observations is provided. Extreme value statistics are applied on merged radar rainfall product covering different area sizes from a single point up to about 1000 km2. The rainfall extremes are supposed to decrease as the area increases. This behavior could not be confirmed by the radar observations. The reason is the limited single-point sampling approach for extreme value analysis. New multiple-point sampling strategies are proposed to mitigate this problem.
Share