Articles | Volume 23, issue 1
https://doi.org/10.5194/hess-23-277-2019
© 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-23-277-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Improving soil moisture and runoff simulations at 3 km over Europe using land surface data assimilation
Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, 52425 Jülich, Germany
Wolfgang Kurtz
Leibniz Supercomputing Centre, Environmental Computing Group, Boltzmannstr. 1, 85748 Garching, Germany
Carsten Montzka
Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52425 Jülich, Germany
Wendy Sharples
Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, 52425 Jülich, Germany
Research Centre Jülich, Jülich Supercomputing Centre, 52425 Jülich, Germany
Klaus Goergen
Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, 52425 Jülich, Germany
Jessica Keune
Laboratory of Hydrology and Water Management, Ghent University, 9000 Ghent, Belgium
Huilin Gao
Zachry Department of Civil Engineering, Texas A & M University, College Station, TX 77843, USA
Anne Springer
Institute of Geodesy and Geoinformation, Bonn University, Nussallee 17, 53115 Bonn, Germany
Harrie-Jan Hendricks Franssen
Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, 52425 Jülich, Germany
Stefan Kollet
Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, 52425 Jülich, Germany
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23 citations as recorded by crossref.
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23 citations as recorded by crossref.
- Deep learning of model- and reanalysis-based precipitation and pressure mismatches over Europe K. Patakchi Yousefi & S. Kollet 10.3389/frwa.2023.1178114
- Pseudo-Spatially-Distributed Modeling of Water Balance Components in the Free State of Saxony T. Luong et al. 10.3390/hydrology7040084
- Quantifying Streamflow Depletion from Groundwater Pumping: A Practical Review of Past and Emerging Approaches for Water Management S. Zipper et al. 10.1111/1752-1688.12998
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- Water table depth assimilation in integrated terrestrial system models at the larger catchment scale F. Li et al. 10.3389/frwa.2023.1150999
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- Assimilating multivariate remote sensing data into a fully coupled subsurface-land surface hydrological model S. Sadat Soltani et al. 10.1016/j.jhydrol.2024.131812
- Climate change effects on hydrometeorological compound events over southern Norway B. Poschlod et al. 10.1016/j.wace.2020.100253
- Unpacking dasymetric modelling to correct spatial bias in environmental model outputs M. Kallio et al. 10.1016/j.envsoft.2022.105511
- Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach T. Boas et al. 10.5194/hess-27-3143-2023
- High spatial resolution simulation of profile soil moisture by assimilating multi-source remote-sensed information into a distributed hydrological model H. Yang et al. 10.1016/j.jhydrol.2021.126311
- Improving the representation of cropland sites in the Community Land Model (CLM) version 5.0 T. Boas et al. 10.5194/gmd-14-573-2021
- A comprehensive assessment of in situ and remote sensing soil moisture data assimilation in the APSIM model for improving agricultural forecasting across the US Midwest M. Kivi et al. 10.5194/hess-27-1173-2023
- A 3 km spatially and temporally consistent European daily soil moisture reanalysis from 2000 to 2015 B. Naz et al. 10.1038/s41597-020-0450-6
- Coupling the Community Land Model version 5.0 to the parallel data assimilation framework PDAF: description and applications L. Strebel et al. 10.5194/gmd-15-395-2022
- Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors H. Beck et al. 10.5194/hess-25-17-2021
- Sensitivity‐Based Soil Moisture Assimilation for Improved Streamflow Forecast Using a Novel Forward Sensitivity Method (FSM) Approach R. Visweshwaran et al. 10.1029/2021WR031092
- Assimilation of Satellite Soil Moisture Products for River Flow Prediction: An Extensive Experiment in Over 700 Catchments Throughout Europe D. De Santis et al. 10.1029/2021WR029643
- Multi-model hydrological reference dataset over continental Europe and an African basin B. Droppers et al. 10.1038/s41597-024-03825-9
- Sensitivity Analysis of C and Ku-Band Scatterometers for River Water Level Estimation A. Kushwaha et al. 10.1109/TGRS.2022.3187173
- Land use change impacts on European heat and drought: remote land-atmosphere feedbacks mitigated locally by shallow groundwater S. Zipper et al. 10.1088/1748-9326/ab0db3
- A Simplified Water Accounting Procedure to Assess Climate Change Impact on Water Resources for Agriculture across Different European River Basins J. Hunink et al. 10.3390/w11101976
- Spatial heterogeneity effects on land surface modeling of water and energy partitioning L. Li et al. 10.5194/gmd-15-5489-2022
Latest update: 20 Nov 2024
Short summary
This study investigates the value of assimilating coarse-resolution remotely sensed soil moisture data into high-resolution land surface models for improving soil moisture and runoff modeling. The soil moisture estimates in this study, with complete spatio-temporal coverage and improved spatial resolution from the assimilation, offer a new reanalysis product for the monitoring of surface soil water content and other hydrological fluxes at 3 km resolution over Europe.
This study investigates the value of assimilating coarse-resolution remotely sensed soil...