PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model
By E. Sutanudjaja, Rens van Beek, N. Wanders, Yoshihide Wada, J. Bosmans, N. Drost, R. J. van der Ent, Inge E. M. de Graaf, J. Hoch, Kor de Jong and 8 more. Geoscientific Model Development, 2017
476 citations recorded by the source corpus.
Abstract. We present PCR-GLOBWB 2, a global hydrology and water resources model. Compared to previous versions of PCR-GLOBWB, this version fully integrates water use. Sector-specific water demand, groundwater and surface water withdrawal, water consumption, and return flows are dynamically calculated at every time step and interact directly with the simulated hydrology. PCR-GLOBWB 2 has been fully rewritten in Python and PCRaster Python and has a modular structure, allowing easier replacement, maintenance, and development of model components. PCR-GLOBWB 2 has been implemented at 5 arcmin resolution, but a version parameterized at 30 arcmin resolution is also available. Both versions are available as open-source codes on https://github.com/UU-Hydro/PCR-GLOBWB_model (Sutanudjaja et al., 2017a). PCR-GLOBWB 2 has its own routines for groundwater dynamics and surface water routing. These relatively simple routines can alternatively be replaced by dynamically coupling PCR-GLOBWB 2 to a global two-layer groundwater model and 1-D–2-D hydrodynamic models. Here, we describe the main components of the model, compare results of the 30 and 5 arcmin versions, and evaluate their model performance using Global Runoff Data Centre discharge data. Results show that model performance of the 5 arcmin version is notably better than that of the 30 arcmin version. Furthermore, we compare simulated time series of total water storage (TWS) of the 5 arcmin model with those observed with GRACE, showing similar negative trends in areas of prevalent groundwater depletion. Also, we find that simulated total water withdrawal matches reasonably well with reported water withdrawal from AQUASTAT, while water withdrawal by source and sector provide mixed results.
Subfields: Geochemistry and Petrology, Ocean Engineering, Oceanography
View Paper: https://www.semanticscholar.org/paper/79fccf76aedde1856f4c290fc0a172618af7cd45
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Citations in the corpus
- Non-renewable groundwater use and groundwater depletion: a review (2019, background): “These are often calculated from hydrology and water resources models (e.g. De Graaf et al 2014, Sutanudjaja et al 2018) which may be subject to considerable uncertainty.”
- Feedback between drought and deforestation in the Amazon (2020, methodology): “As in Staal et al. (2018) [29], due to limited availability of data that are consistent across the different models that we used, we only analyze the period between 2003‒2014: atmospheric data pre-2003 have discrepancies with those from 2003 onward due to differences in the data sources [42], and th”