Articles | Volume 21, issue 3
https://doi.org/10.5194/hess-21-1769-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-1769-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A high-resolution dataset of water fluxes and states for Germany accounting for parametric uncertainty
Helmholtz Centre for Environmental Research – UFZ, Department
Computational Hydrosystems, Permoserstraße 15, 04318 Leipzig, Germany
Rohini Kumar
Helmholtz Centre for Environmental Research – UFZ, Department
Computational Hydrosystems, Permoserstraße 15, 04318 Leipzig, Germany
Matthias Cuntz
Helmholtz Centre for Environmental Research – UFZ, Department
Computational Hydrosystems, Permoserstraße 15, 04318 Leipzig, Germany
INRA, Université de Lorraine, UMR1137 Ecologie et Ecophysiologie
Forestières, Champenoux, France
Helmholtz Centre for Environmental Research – UFZ, Department
Computational Hydrosystems, Permoserstraße 15, 04318 Leipzig, Germany
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- Emergence of heavy tails in streamflow distributions: the role of spatial rainfall variability H. Wang et al. 10.1016/j.advwatres.2022.104359
- Challenges in Applying Machine Learning Models for Hydrological Inference: A Case Study for Flooding Events Across Germany L. Schmidt et al. 10.1029/2019WR025924
- Inferring Grassland Drought Stress with Unsupervised Learning from Airborne Hyperspectral VNIR Imagery F. Hermanns et al. 10.3390/rs13101885
- High-resolution impact-based early warning system for riverine flooding H. Najafi et al. 10.1038/s41467-024-48065-y
- Spatial Organization of Human Population and Wastewater Treatment Plants in Urbanized River Basins S. Yang et al. 10.1029/2018WR024614
- Disentangling the Impact of Catchment Heterogeneity on Nitrate Export Dynamics From Event to Long‐Term Time Scales C. Winter et al. 10.1029/2020WR027992
- A drought monitoring tool for South Asia T. Saha et al. 10.1088/1748-9326/abf525
- The multiscale routing model mRM v1.0: simple river routing at resolutions from 1 to 50 km S. Thober et al. 10.5194/gmd-12-2501-2019
- Assessment of groundwater recharge for a coarse-gravel porous aquifer in Slovenia V. Zupanc et al. 10.1007/s10040-020-02152-8
- The effect of soil moisture anomalies on maize yield in Germany M. Peichl et al. 10.5194/nhess-18-889-2018
Latest update: 16 Nov 2024
Short summary
We discuss the estimation of a long-term, high-resolution, continuous and consistent dataset of hydro-meteorological variables for Germany. Here we describe the derivation of national-scale parameter sets and analyze the uncertainty of the estimated hydrologic variables (focusing on the parametric uncertainty). Our study highlights the role of accounting for the parametric uncertainty in model-derived hydrological datasets.
We discuss the estimation of a long-term, high-resolution, continuous and consistent dataset of...