Global Fully Distributed Parameter Regionalization Based on Observed Streamflow From 4,229 Headwater Catchments

Hylke E. Beck; Ming Pan; Peirong Lin; Jan Seibert; Albert I.J.M. van Dijk; Eric F. Wood

doi:10.1029/2019JD031485

Global Fully Distributed Parameter Regionalization Based on Observed Streamflow From 4,229 Headwater Catchments

Hylke E. Beck, Ming Pan, Peirong Lin, Jan Seibert, Albert I.J.M. van Dijk, Eric F. Wood

Research output: Contribution to journal › Article › peer-review

63 Scopus citations

Abstract

All hydrological models need to be calibrated to obtain satisfactory streamflow simulations. Here we present a novel parameter regionalization approach that involves the optimization of transfer equations linking model parameters to climate and landscape characteristics. The optimization was performed in a fully spatially distributed fashion at high resolution (0.05°), instead of at lumped catchment scale, using an unprecedented database of daily observed streamflow from 4,229 headwater catchments (

Original language	English (US)
Journal	Journal of Geophysical Research: Atmospheres
Volume	125
Issue number	17
DOIs	https://doi.org/10.1029/2019JD031485
State	Published - Sep 16 2020
Externally published	Yes

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10.1029/2019JD031485

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AU - Beck, Hylke E.

AU - Pan, Ming

AU - Lin, Peirong

AU - Seibert, Jan

AU - van Dijk, Albert I.J.M.

AU - Wood, Eric F.

N1 - Generated from Scopus record by KAUST IRTS on 2023-02-14

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N2 - All hydrological models need to be calibrated to obtain satisfactory streamflow simulations. Here we present a novel parameter regionalization approach that involves the optimization of transfer equations linking model parameters to climate and landscape characteristics. The optimization was performed in a fully spatially distributed fashion at high resolution (0.05°), instead of at lumped catchment scale, using an unprecedented database of daily observed streamflow from 4,229 headwater catchments (

AB - All hydrological models need to be calibrated to obtain satisfactory streamflow simulations. Here we present a novel parameter regionalization approach that involves the optimization of transfer equations linking model parameters to climate and landscape characteristics. The optimization was performed in a fully spatially distributed fashion at high resolution (0.05°), instead of at lumped catchment scale, using an unprecedented database of daily observed streamflow from 4,229 headwater catchments (

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ER -

Global Fully Distributed Parameter Regionalization Based on Observed Streamflow From 4,229 Headwater Catchments

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