Articles | Volume 15, issue 19
https://doi.org/10.5194/gmd-15-7287-2022
© 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-15-7287-2022
© 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
| 
04 Oct 2022
Model description paper |
| 04 Oct 2022
| 04 Oct 2022
Water balance model (WBM) v.1.0.0: a scalable gridded global hydrologic model with water-tracking functionality
Danielle S. Grogan
CORRESPONDING AUTHOR
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Alex Prusevich
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Wilfred M. Wollheim
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Department of Natural Resources and the Environment, University of New
Hampshire, NH 03824, USA
Stanley Glidden
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Richard B. Lammers
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
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- Wetter trend in source region of Yangtze River by runoff simulating based on Grid-RCCC-WBM Z. Ning et al. 10.1016/j.jhydrol.2024.130702
- Local land‐use decisions drive losses in river biological integrity to 2099: Using machine learning to disentangle interacting drivers of ecological change in policy forecasts K. Bourne et al. 10.1002/met.70024
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- Macroscale composite principal-monotonicity distributed projection of climate-induced hydrologic changes: Tempo-spatial variabilities, and variation decompositions G. Cheng et al. 10.1016/j.jhydrol.2023.130246
- Distinguishing Direct Human‐Driven Effects on the Global Terrestrial Water Cycle E. Kåresdotter et al. 10.1029/2022EF002848
20 citations as recorded by crossref.
- Optimizing urban green infrastructure using a highly detailed surface modeling approach A. Addas 10.1007/s43621-024-00266-7
- Enhancing the representation of water management in global hydrological models G. Abeshu et al. 10.5194/gmd-16-5449-2023
- Fusing Climate Data Products Using a Spatially Varying Autoencoder J. Johnson et al. 10.1007/s13253-024-00657-3
- A Scientometric Analysis of Research Trends and Knowledge Structure on the Climate Effects of Irrigation between 1993 and 2022 S. Huang et al. 10.3390/agronomy13102482
- Water Use in Livestock Agri-Food Systems and Its Contribution to Local Water Scarcity: A Spatially Distributed Global Analysis D. Wisser et al. 10.3390/w16121681
- The benefits and trade-offs of multi-variable calibration of the WaterGAP global hydrological model (WGHM) in the Ganges and Brahmaputra basins H. Hasan et al. 10.5194/hess-29-567-2025
- Harmonized Database of Western U.S. Water Rights (HarDWR) v.1 M. Lisk et al. 10.1038/s41597-024-03434-6
- Hydroeconomic insights for transboundary water challenges and potential collaboration in the Tigris-Euphrates river basin F. Taheripour et al. 10.1088/2515-7620/ad94d7
- Local, regional, and global adaptations to a compound pandemic-weather stress event I. Haqiqi et al. 10.1088/1748-9326/acbbe3
- Global-scale evaluation of precipitation datasets for hydrological modelling S. Gebrechorkos et al. 10.5194/hess-28-3099-2024
- Delineation of endorheic drainage basins in the MERIT-Plus dataset for 5 and 15 minute upscaled river networks A. Prusevich et al. 10.1038/s41597-023-02875-9
- Wetter trend in source region of Yangtze River by runoff simulating based on Grid-RCCC-WBM Z. Ning et al. 10.1016/j.jhydrol.2024.130702
- Local land‐use decisions drive losses in river biological integrity to 2099: Using machine learning to disentangle interacting drivers of ecological change in policy forecasts K. Bourne et al. 10.1002/met.70024
- Machine learning-enabled calibration of river routing model parameters Y. Zhao et al. 10.2166/hydro.2023.030
- Climate-driven shifts in freshwater biodiversity will impact mitigation costs for hydropower H. Yoon et al. 10.1016/j.scitotenv.2024.176201
- Effectiveness and Distributional Impacts of Conservation Policies: The Role of Labor Markets S. Ray & T. Hertel 10.1007/s10640-024-00950-2
- Existing wetland conservation programs miss nutrient reduction targets S. Zuidema et al. 10.1093/pnasnexus/pgae129
- Representing farmer irrigated crop area adaptation in a large-scale hydrological model J. Yoon et al. 10.5194/hess-28-899-2024
- US climate policy yields water quality cobenefits in the Mississippi Basin and Gulf of Mexico S. Zuidema et al. 10.1073/pnas.2302087120
- Macroscale composite principal-monotonicity distributed projection of climate-induced hydrologic changes: Tempo-spatial variabilities, and variation decompositions G. Cheng et al. 10.1016/j.jhydrol.2023.130246
1 citations as recorded by crossref.
Latest update: 23 Apr 2025
Short summary
This paper describes the University of New Hampshire's water balance model (WBM). This model simulates the land surface components of the global water cycle and includes water extractions for use by humans for agricultural, domestic, and industrial purposes. A new feature is described that permits water source tracking through the water cycle, which has implications for water resource management. This paper was written to describe a long-used model and presents its first open-source version.
This paper describes the University of New Hampshire's water balance model (WBM). This model...
