Articles | Volume 23, issue 7
https://doi.org/10.5194/hess-23-2863-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-2863-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jul 2019
Research article |
| 08 Jul 2019
| 08 Jul 2019
Assessment of spatial uncertainty of heavy rainfall at catchment scale using a dense gauge network
Institute for Geophysics, Astrophysics, and Meteorology/Institute of Physics (IGAM/IP), NAWI Graz, University of Graz, Graz, Austria
FWF-DK Climate Change, University of Graz, Austria
now at: Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Ulrich Foelsche
Institute for Geophysics, Astrophysics, and Meteorology/Institute of Physics (IGAM/IP), NAWI Graz, University of Graz, Graz, Austria
FWF-DK Climate Change, University of Graz, Austria
Wegener Center for Climate and Global Change (WEGC), University of Graz, Graz, Austria
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- Advancing Characterization and Modeling of Space-Time Correlation Structure and Marginal Distribution of Short-Duration Precipitation G. Mascaro et al. https://doi.org/10.1016/j.advwatres.2023.104451
- Exploring possible climate change amplification of warm-season precipitation extremes in the southeastern Alpine forelands at regional to local scales S. Haas et al. https://doi.org/10.1016/j.ejrh.2024.101987
- Climate Models Permit Convection at Much Coarser Resolutions Than Previously Considered J. Vergara-Temprado et al. https://doi.org/10.1175/JCLI-D-19-0286.1
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- The evaluation and downscaling‐calibration of IMERG precipitation products at sub‐daily scales over a metropolitan region Q. Zhuang et al. https://doi.org/10.1111/jfr3.12902
- Stochastic Parameters of Flash Floods Formation in the North of the Black Sea Coast L. Kuksina et al. https://doi.org/10.31857/S0869607123020064
- Probabilistic connectivity assessment of road networks exposed to spatially correlated rainfall-triggered landslides Z. He et al. https://doi.org/10.1016/j.ress.2025.110800
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- Assessment of two approaches for very short range precipitation prediction for a convection-dominant period at different scales E. Ghaemi et al. https://doi.org/10.1016/j.atmosres.2024.107522
- Quantifying rainfall variability and potential hazards of extreme events in Beijing through stochastic simulations T. Li et al. https://doi.org/10.1016/j.ejrh.2025.103068
- Rainfall spatial-heterogeneity accelerates landscape evolution processes N. Peleg et al. https://doi.org/10.1016/j.geomorph.2021.107863
- Analysis and verification of reconstructed historical extreme precipitation events in an hourly resolution V. Bližňák et al. https://doi.org/10.1016/j.atmosres.2020.105309
- Integrated Rainfall Estimation Using Rain Gauges and Weather Radar: Implications for Rainfall-Induced Landslides M. De Biase et al. https://doi.org/10.3390/rs17213629
- Analysing the Large-Scale Debris Flow Event in July 2022 in Horlachtal, Austria Using Remote Sensing and Measurement Data J. Rom et al. https://doi.org/10.3390/geosciences13040100
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26 citations as recorded by crossref.
- Geographical landslide early warning systems F. Guzzetti et al. https://doi.org/10.1016/j.earscirev.2019.102973
- Small Catchment Runoff Sensitivity to Station Density and Spatial Interpolation: Hydrological Modeling of Heavy Rainfall Using a Dense Rain Gauge Network C. Hohmann et al. https://doi.org/10.3390/w13101381
- Flash floods on the northern coast of the Black Sea: Formation and characteristics L. Kuksina et al. https://doi.org/10.1016/j.ijsrc.2024.10.003
- Predicting pluvial flood impacts in data-scarce urban environments: Uncertainty and interplay between rainfall inputs and conceptual drainage loss models P. Costabile et al. https://doi.org/10.1016/j.uclim.2025.102724
- WegenerNet high-resolution weather and climate data from 2007 to 2020 J. Fuchsberger et al. https://doi.org/10.5194/essd-13-1307-2021
- A Convolutional Neural Network Algorithm for Soil Moisture Prediction from Sentinel-1 SAR Images E. Hegazi et al. https://doi.org/10.3390/rs13244964
- Temperature effects on the spatial structure of heavy rainfall modify catchment hydro-morphological response N. Peleg et al. https://doi.org/10.5194/esurf-8-17-2020
- Hydrological performance of bioretention in field experiments and models: A review from the perspective of design characteristics and local contexts T. Huang et al. https://doi.org/10.1016/j.scitotenv.2025.178684
- Evaluation of GPM-DPR precipitation estimates with WegenerNet gauge data M. Lasser et al. https://doi.org/10.5194/amt-12-5055-2019
- Gridded daily precipitation data for Iran: A comparison of different methods A. Bárdossy et al. https://doi.org/10.1016/j.ejrh.2021.100958
- Advancing Characterization and Modeling of Space-Time Correlation Structure and Marginal Distribution of Short-Duration Precipitation G. Mascaro et al. https://doi.org/10.1016/j.advwatres.2023.104451
- Exploring possible climate change amplification of warm-season precipitation extremes in the southeastern Alpine forelands at regional to local scales S. Haas et al. https://doi.org/10.1016/j.ejrh.2024.101987
- Climate Models Permit Convection at Much Coarser Resolutions Than Previously Considered J. Vergara-Temprado et al. https://doi.org/10.1175/JCLI-D-19-0286.1
- Assessment of spatial variability of precipitation in Krishna River Basin using a metric based on apportionment entropy S. Chetan Kumar et al. https://doi.org/10.1080/02626667.2024.2376708
- The evaluation and downscaling‐calibration of IMERG precipitation products at sub‐daily scales over a metropolitan region Q. Zhuang et al. https://doi.org/10.1111/jfr3.12902
- Stochastic Parameters of Flash Floods Formation in the North of the Black Sea Coast L. Kuksina et al. https://doi.org/10.31857/S0869607123020064
- Probabilistic connectivity assessment of road networks exposed to spatially correlated rainfall-triggered landslides Z. He et al. https://doi.org/10.1016/j.ress.2025.110800
- Saudi Rainfall (SaRa): hourly 0.1° gridded rainfall (1979–present) for Saudi Arabia via machine learning fusion of satellite and model data X. Wang et al. https://doi.org/10.5194/hess-29-4983-2025
- A regional early warning model of geological hazards based on big data of real-time rainfall W. Zhao et al. https://doi.org/10.1007/s11069-023-05819-z
- Assessment of two approaches for very short range precipitation prediction for a convection-dominant period at different scales E. Ghaemi et al. https://doi.org/10.1016/j.atmosres.2024.107522
- Quantifying rainfall variability and potential hazards of extreme events in Beijing through stochastic simulations T. Li et al. https://doi.org/10.1016/j.ejrh.2025.103068
- Rainfall spatial-heterogeneity accelerates landscape evolution processes N. Peleg et al. https://doi.org/10.1016/j.geomorph.2021.107863
- Analysis and verification of reconstructed historical extreme precipitation events in an hourly resolution V. Bližňák et al. https://doi.org/10.1016/j.atmosres.2020.105309
- Integrated Rainfall Estimation Using Rain Gauges and Weather Radar: Implications for Rainfall-Induced Landslides M. De Biase et al. https://doi.org/10.3390/rs17213629
- Analysing the Large-Scale Debris Flow Event in July 2022 in Horlachtal, Austria Using Remote Sensing and Measurement Data J. Rom et al. https://doi.org/10.3390/geosciences13040100
- Evaluation of Integrated Nowcasting through Comprehensive Analysis (INCA) precipitation analysis using a dense rain-gauge network in southeastern Austria E. Ghaemi et al. https://doi.org/10.5194/hess-25-4335-2021
Saved (final revised paper)
Latest update: 28 May 2026
Short summary
We analyze heavy local rainfall to address questions regarding the spatial uncertainty due to the approximation of areal rainfall using point measurements. Ten years of rainfall data from a dense network of 150 rain gauges in southeastern Austria are employed, which permits robust examination of small-scale rainfall at various horizontal resolutions. Quantitative uncertainty information from the study can guide both data users and producers to estimate uncertainty in their own rainfall dataset.
We analyze heavy local rainfall to address questions regarding the spatial uncertainty due to...
