Articles | Volume 14, issue 9
https://doi.org/10.5194/essd-14-4035-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-4035-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
06 Sep 2022
Data description paper |
| 06 Sep 2022
| 06 Sep 2022
A 500-year annual runoff reconstruction for 14 selected European catchments
Sadaf Nasreen
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Suchdol, Prague 16500, Czech Republic
Markéta Součková
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Suchdol, Prague 16500, Czech Republic
Mijael Rodrigo Vargas Godoy
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Suchdol, Prague 16500, Czech Republic
Ujjwal Singh
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Suchdol, Prague 16500, Czech Republic
Yannis Markonis
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Suchdol, Prague 16500, Czech Republic
Rohini Kumar
UFZ-Helmholtz Centre for Environmental Research, 04318 Leipzig, Germany
Oldrich Rakovec
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Suchdol, Prague 16500, Czech Republic
UFZ-Helmholtz Centre for Environmental Research, 04318 Leipzig, Germany
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Suchdol, Prague 16500, Czech Republic
T. G. Masaryk Water Research Institute, p.r.i., Prague 16000, Czech Republic
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Cited
11 citations as recorded by crossref.
- CH-RUN: a deep-learning-based spatially contiguous runoff reconstruction for Switzerland B. Kraft et al. 10.5194/hess-29-1061-2025
- Regional Reconstruction of Po River Basin (Italy) Streamflow G. Formetta et al. 10.3390/hydrology9100163
- Groundwater level reconstruction using long-term climate reanalysis data and deep neural networks S. Chidepudi et al. 10.1016/j.ejrh.2023.101632
- Streamflow Reconstructions Using Tree-Ring-Based Paleo Proxies for the Sava River Basin (Slovenia) G. Tootle et al. 10.3390/hydrology10070138
- Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations Y. Zhang et al. 10.5194/hess-27-4529-2023
- Hybrid multi-model ensemble learning for reconstructing gridded runoff of Europe for 500 years U. Singh et al. 10.1016/j.inffus.2023.101807
- Extraordinary 21st Century Drought in the Po River Basin (Italy) A. Ramírez Molina et al. 10.3390/hydrology11120219
- Multiple temporal scale variation characteristics and driving factors of arid inland runoff: A case study of Urumqi River, China K. Liu et al. 10.1016/j.ejrh.2025.102298
- Long-term analysis of changes in seasonal and maximum discharges of Slovak rivers in the period 1931–2020 V. Mitková et al. 10.2478/johh-2024-0030
- Stochastic Analysis of the Marginal and Dependence Structure of Streamflows: From Fine-Scale Records to Multi-Centennial Paleoclimatic Reconstructions A. Pizarro et al. 10.3390/hydrology9070126
- Streamflow Reconstructions Using Tree-Ring Based Paleo Proxies for the Upper Adige River Basin (Italy) G. Formetta et al. 10.3390/hydrology9010008
9 citations as recorded by crossref.
- CH-RUN: a deep-learning-based spatially contiguous runoff reconstruction for Switzerland B. Kraft et al. 10.5194/hess-29-1061-2025
- Regional Reconstruction of Po River Basin (Italy) Streamflow G. Formetta et al. 10.3390/hydrology9100163
- Groundwater level reconstruction using long-term climate reanalysis data and deep neural networks S. Chidepudi et al. 10.1016/j.ejrh.2023.101632
- Streamflow Reconstructions Using Tree-Ring-Based Paleo Proxies for the Sava River Basin (Slovenia) G. Tootle et al. 10.3390/hydrology10070138
- Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations Y. Zhang et al. 10.5194/hess-27-4529-2023
- Hybrid multi-model ensemble learning for reconstructing gridded runoff of Europe for 500 years U. Singh et al. 10.1016/j.inffus.2023.101807
- Extraordinary 21st Century Drought in the Po River Basin (Italy) A. Ramírez Molina et al. 10.3390/hydrology11120219
- Multiple temporal scale variation characteristics and driving factors of arid inland runoff: A case study of Urumqi River, China K. Liu et al. 10.1016/j.ejrh.2025.102298
- Long-term analysis of changes in seasonal and maximum discharges of Slovak rivers in the period 1931–2020 V. Mitková et al. 10.2478/johh-2024-0030
2 citations as recorded by crossref.
- Stochastic Analysis of the Marginal and Dependence Structure of Streamflows: From Fine-Scale Records to Multi-Centennial Paleoclimatic Reconstructions A. Pizarro et al. 10.3390/hydrology9070126
- Streamflow Reconstructions Using Tree-Ring Based Paleo Proxies for the Upper Adige River Basin (Italy) G. Formetta et al. 10.3390/hydrology9010008
Latest update: 01 Apr 2025
Short summary
This article presents a 500-year reconstructed annual runoff dataset for several European catchments. Several data-driven and hydrological models were used to derive the runoff series using reconstructed precipitation and temperature and a set of proxy data. The simulated runoff was validated using independent observed runoff data and documentary evidence. The validation revealed a good fit between the observed and reconstructed series for 14 catchments, which are available for further analysis.
This article presents a 500-year reconstructed annual runoff dataset for several European...
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