Articles | Volume 15, issue 2
https://doi.org/10.5194/gmd-15-859-2022
© 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/gmd-15-859-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
31 Jan 2022
Model description paper |
| 31 Jan 2022
| 31 Jan 2022
MPR 1.0: a stand-alone multiscale parameter regionalization tool for improved parameter estimation of land surface models
Robert Schweppe
Helmholtz-Centre for Environmental Research – UFZ, Permoserstraße 15, 04315 Leipzig, Germany
Institute of Earth and Environmental Science, University of Potsdam, Karl-Liebknecht-Str. 24–25,
14476 Potsdam-Golm, Germany
Helmholtz-Centre for Environmental Research – UFZ, Permoserstraße 15, 04315 Leipzig, Germany
Sebastian Müller
Helmholtz-Centre for Environmental Research – UFZ, Permoserstraße 15, 04315 Leipzig, Germany
Matthias Kelbling
Helmholtz-Centre for Environmental Research – UFZ, Permoserstraße 15, 04315 Leipzig, Germany
Rohini Kumar
Helmholtz-Centre for Environmental Research – UFZ, Permoserstraße 15, 04315 Leipzig, Germany
Sabine Attinger
Helmholtz-Centre for Environmental Research – UFZ, Permoserstraße 15, 04315 Leipzig, Germany
Institute of Earth and Environmental Science, University of Potsdam, Karl-Liebknecht-Str. 24–25,
14476 Potsdam-Golm, Germany
Luis Samaniego
Helmholtz-Centre for Environmental Research – UFZ, Permoserstraße 15, 04315 Leipzig, Germany
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19 citations as recorded by crossref.
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- Estimation of spatiotemporally varying parameters for grid-based distributed hydrologic models X. Zhang et al. 10.1016/j.ejrh.2025.102536
- Regionalization in global hydrological models and its impact on runoff simulations: a case study using WaterGAP3 (v 1.0.0) J. Kupzig et al. 10.5194/gmd-17-6819-2024
- On the use of distributed hydrologic model for filling large gaps at different parts of the streamflow data E. Ergün & M. Demirel 10.1016/j.jestch.2022.101321
- Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest B. Bahrami et al. 10.5194/gmd-15-6957-2022
- Improving runoff simulation in the Western United States with Noah-MP and VIC models L. Su et al. 10.5194/hess-28-3079-2024
- Does dynamically modeled leaf area improve predictions of land surface water and carbon fluxes? Insights into dynamic vegetation modules S. Westermann et al. 10.5194/bg-21-5277-2024
- An inter-comparison of approaches and frameworks to quantify irrigation from satellite data S. Kragh et al. 10.5194/hess-28-441-2024
- Parameter regionalization of large-scale distributed rainfall–runoff models using a conditional probability method T. Sayama et al. 10.1186/s40645-025-00691-w
- A data-centric perspective on the information needed for hydrological uncertainty predictions A. Auer et al. 10.5194/hess-28-4099-2024
- Effects of Model Spatial Structure and Basin Characteristics on the Performance of Three Hydrologic Models F. Kacar et al. 10.1007/s11269-025-04308-1
- Automatic Regionalization of Model Parameters for Hydrological Models M. Feigl et al. 10.1029/2022WR031966
18 citations as recorded by crossref.
- Model parameterization scheme for a distributed hydrological model, BTOPMC S. Bastola 10.1016/j.hydres.2025.06.001
- Effect of Model Structure and Calibration Algorithm on Discharge Simulation in the Acısu Basin, Turkey H. Alp et al. 10.3390/cli10120196
- Tradeoffs Between Temporal and Spatial Pattern Calibration and Their Impacts on Robustness and Transferability of Hydrologic Model Parameters to Ungauged Basins M. Demirel et al. 10.1029/2022WR034193
- Testing the mHM-MPR Reliability for Parameter Transferability across Locations in North–Central Nigeria K. Ogbu et al. 10.3390/hydrology9090158
- Towards parameter estimation in global hydrological models J. Kupzig et al. 10.1088/1748-9326/acdae8
- Integrating Convolutional Attention and Encoder–Decoder Long Short-Term Memory for Enhanced Soil Moisture Prediction J. Han et al. 10.3390/w16233481
- Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model E. Fatima et al. 10.5194/hess-28-5419-2024
- Hydrological Impact of the New ECMWF Multi-Layer Snow Scheme E. Zsoter et al. 10.3390/atmos13050727
- Estimation of spatiotemporally varying parameters for grid-based distributed hydrologic models X. Zhang et al. 10.1016/j.ejrh.2025.102536
- Regionalization in global hydrological models and its impact on runoff simulations: a case study using WaterGAP3 (v 1.0.0) J. Kupzig et al. 10.5194/gmd-17-6819-2024
- On the use of distributed hydrologic model for filling large gaps at different parts of the streamflow data E. Ergün & M. Demirel 10.1016/j.jestch.2022.101321
- Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest B. Bahrami et al. 10.5194/gmd-15-6957-2022
- Improving runoff simulation in the Western United States with Noah-MP and VIC models L. Su et al. 10.5194/hess-28-3079-2024
- Does dynamically modeled leaf area improve predictions of land surface water and carbon fluxes? Insights into dynamic vegetation modules S. Westermann et al. 10.5194/bg-21-5277-2024
- An inter-comparison of approaches and frameworks to quantify irrigation from satellite data S. Kragh et al. 10.5194/hess-28-441-2024
- Parameter regionalization of large-scale distributed rainfall–runoff models using a conditional probability method T. Sayama et al. 10.1186/s40645-025-00691-w
- A data-centric perspective on the information needed for hydrological uncertainty predictions A. Auer et al. 10.5194/hess-28-4099-2024
- Effects of Model Spatial Structure and Basin Characteristics on the Performance of Three Hydrologic Models F. Kacar et al. 10.1007/s11269-025-04308-1
1 citations as recorded by crossref.
Latest update: 29 Jul 2025
Short summary
The recently released multiscale parameter regionalization (MPR) tool enables
environmental modelers to efficiently use extensive datasets for model setups.
It flexibly ingests the datasets using user-defined data–parameter relationships
and rescales parameter fields to given model resolutions. Modern
land surface models especially benefit from MPR through increased transparency and
flexibility in modeling decisions. Thus, MPR empowers more sound and robust
simulations of the Earth system.
The recently released multiscale parameter regionalization (MPR) tool enables
environmental...
