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Global-scale regionalization of hydrologic model parameters

(2016) WATER RESOURCES RESEARCH. 52(5). p.3599-3622
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Abstract
Current state-of-the-art models typically applied at continental to global scales (hereafter called macroscale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments ( 10-10,000 km(2)) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.5 degrees grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the 10 most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially uniform (i.e., averaged calibrated) parameters for 79% of the evaluation catchments. Substantial improvements were evident for all major Koppen-Geiger climate types and even for evaluation catchments>5000 km distant from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV with regionalized parameters outperformed nine state-of-the-art macroscale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via .
Keywords
CLIMATE-CHANGE, WATER-BALANCE, calibration, runoff, discharge, ensemble, rainfall-runoff, parameters, RAINFALL-RUNOFF MODELS, LAND-SURFACE MODELS, UNGAUGED CATCHMENTS, RIVER-BASIN, EVOLUTIONARY ALGORITHMS, CONTINUOUS STREAMFLOW, TROPICAL CATCHMENTS, SOIL-MOISTURE

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Citation

Please use this url to cite or link to this publication:

MLA
Beck, Hylke E et al. “Global-scale Regionalization of Hydrologic Model Parameters.” WATER RESOURCES RESEARCH 52.5 (2016): 3599–3622. Print.
APA
Beck, H. E., van Dijk, A. I., de Roo, A., Gonzalez Miralles, D., McVicar, T. R., Schellekens, J., & Bruijnzeel, L. A. (2016). Global-scale regionalization of hydrologic model parameters. WATER RESOURCES RESEARCH, 52(5), 3599–3622.
Chicago author-date
Beck, Hylke E, Albert IJM van Dijk, Ad de Roo, Diego Gonzalez Miralles, Tim R McVicar, Jaap Schellekens, and L Adrian Bruijnzeel. 2016. “Global-scale Regionalization of Hydrologic Model Parameters.” Water Resources Research 52 (5): 3599–3622.
Chicago author-date (all authors)
Beck, Hylke E, Albert IJM van Dijk, Ad de Roo, Diego Gonzalez Miralles, Tim R McVicar, Jaap Schellekens, and L Adrian Bruijnzeel. 2016. “Global-scale Regionalization of Hydrologic Model Parameters.” Water Resources Research 52 (5): 3599–3622.
Vancouver
1.
Beck HE, van Dijk AI, de Roo A, Gonzalez Miralles D, McVicar TR, Schellekens J, et al. Global-scale regionalization of hydrologic model parameters. WATER RESOURCES RESEARCH. 2016;52(5):3599–622.
IEEE
[1]
H. E. Beck et al., “Global-scale regionalization of hydrologic model parameters,” WATER RESOURCES RESEARCH, vol. 52, no. 5, pp. 3599–3622, 2016.
@article{7775175,
  abstract     = {Current state-of-the-art models typically applied at continental to global scales (hereafter called macroscale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments ( 10-10,000 km(2)) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.5 degrees grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the 10 most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially uniform (i.e., averaged calibrated) parameters for 79% of the evaluation catchments. Substantial improvements were evident for all major Koppen-Geiger climate types and even for evaluation catchments>5000 km distant from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV with regionalized parameters outperformed nine state-of-the-art macroscale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via .},
  author       = {Beck, Hylke E and van Dijk, Albert IJM and de Roo, Ad and Gonzalez Miralles, Diego and McVicar, Tim R and Schellekens, Jaap and Bruijnzeel, L Adrian},
  issn         = {0043-1397},
  journal      = {WATER RESOURCES RESEARCH},
  keywords     = {CLIMATE-CHANGE,WATER-BALANCE,calibration,runoff,discharge,ensemble,rainfall-runoff,parameters,RAINFALL-RUNOFF MODELS,LAND-SURFACE MODELS,UNGAUGED CATCHMENTS,RIVER-BASIN,EVOLUTIONARY ALGORITHMS,CONTINUOUS STREAMFLOW,TROPICAL CATCHMENTS,SOIL-MOISTURE},
  language     = {eng},
  number       = {5},
  pages        = {3599--3622},
  title        = {Global-scale regionalization of hydrologic model parameters},
  url          = {http://dx.doi.org/10.1002/2015WR018247},
  volume       = {52},
  year         = {2016},
}

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