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A global streamflow reanalysis for 1980–2018

Global and continental scale hydrological reanalysis datasets receive growing attention due to their increasing number of applications, ranging from water resources management, climate change studies, water related hazards and policy support. Until recently, their use was mostly limited to qualitati...

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Detalles Bibliográficos
Autores principales: Alfieri, Lorenzo, Lorini, Valerio, Hirpa, Feyera A., Harrigan, Shaun, Zsoter, Ervin, Prudhomme, Christel, Salamon, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988497/
https://www.ncbi.nlm.nih.gov/pubmed/32025657
http://dx.doi.org/10.1016/j.hydroa.2019.100049
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author Alfieri, Lorenzo
Lorini, Valerio
Hirpa, Feyera A.
Harrigan, Shaun
Zsoter, Ervin
Prudhomme, Christel
Salamon, Peter
author_facet Alfieri, Lorenzo
Lorini, Valerio
Hirpa, Feyera A.
Harrigan, Shaun
Zsoter, Ervin
Prudhomme, Christel
Salamon, Peter
author_sort Alfieri, Lorenzo
collection PubMed
description Global and continental scale hydrological reanalysis datasets receive growing attention due to their increasing number of applications, ranging from water resources management, climate change studies, water related hazards and policy support. Until recently, their use was mostly limited to qualitative assessments, due to their coarse spatial and temporal resolution, large uncertainty and bias in the model output, and limited extent of the dataset in space and time. This research reports on the setup of a gridded hydrological model with quasi-global coverage, able to reproduce a seamless 39-year streamflow simulation in all world’s medium to large river basins. The model was calibrated at 1226 river sections with a total drainage area of 51 million km(2) within 66 countries, using ECMWF’s latest atmospheric reanalysis ERA5. A performance assessment revealed large improvements in reproducing past discharge observations, in comparison to the calibration used in the current operational setup of the hydrological model as part of the Copernicus – Global Flood Awareness System (GloFAS, www.globalfloods.eu), with median scores of Kling-Gupta Efficiency KGE = 0.67 and correlation r = 0.8. The simulation bias was also dramatically reduced and narrowed around zero, with more than 60% of stations showing percent bias within ±20%. Pronounced regional differences in the simulation results remain, pointing out the need for detailed investigation of the hydrological processes in specific regions, including parts of Africa and South Asia. In addition, observed discharges with high data quality is key to achieving skillful model output. The new calibrated model will become part of the operational runs of GloFAS in the next system release foreseen for Spring 2020, together with a near real time extension of the streamflow reanalysis.
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spelling pubmed-69884972020-02-03 A global streamflow reanalysis for 1980–2018 Alfieri, Lorenzo Lorini, Valerio Hirpa, Feyera A. Harrigan, Shaun Zsoter, Ervin Prudhomme, Christel Salamon, Peter J Hydrol X Article Global and continental scale hydrological reanalysis datasets receive growing attention due to their increasing number of applications, ranging from water resources management, climate change studies, water related hazards and policy support. Until recently, their use was mostly limited to qualitative assessments, due to their coarse spatial and temporal resolution, large uncertainty and bias in the model output, and limited extent of the dataset in space and time. This research reports on the setup of a gridded hydrological model with quasi-global coverage, able to reproduce a seamless 39-year streamflow simulation in all world’s medium to large river basins. The model was calibrated at 1226 river sections with a total drainage area of 51 million km(2) within 66 countries, using ECMWF’s latest atmospheric reanalysis ERA5. A performance assessment revealed large improvements in reproducing past discharge observations, in comparison to the calibration used in the current operational setup of the hydrological model as part of the Copernicus – Global Flood Awareness System (GloFAS, www.globalfloods.eu), with median scores of Kling-Gupta Efficiency KGE = 0.67 and correlation r = 0.8. The simulation bias was also dramatically reduced and narrowed around zero, with more than 60% of stations showing percent bias within ±20%. Pronounced regional differences in the simulation results remain, pointing out the need for detailed investigation of the hydrological processes in specific regions, including parts of Africa and South Asia. In addition, observed discharges with high data quality is key to achieving skillful model output. The new calibrated model will become part of the operational runs of GloFAS in the next system release foreseen for Spring 2020, together with a near real time extension of the streamflow reanalysis. Elsevier B.V 2020-01 /pmc/articles/PMC6988497/ /pubmed/32025657 http://dx.doi.org/10.1016/j.hydroa.2019.100049 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Alfieri, Lorenzo
Lorini, Valerio
Hirpa, Feyera A.
Harrigan, Shaun
Zsoter, Ervin
Prudhomme, Christel
Salamon, Peter
A global streamflow reanalysis for 1980–2018
title A global streamflow reanalysis for 1980–2018
title_full A global streamflow reanalysis for 1980–2018
title_fullStr A global streamflow reanalysis for 1980–2018
title_full_unstemmed A global streamflow reanalysis for 1980–2018
title_short A global streamflow reanalysis for 1980–2018
title_sort global streamflow reanalysis for 1980–2018
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988497/
https://www.ncbi.nlm.nih.gov/pubmed/32025657
http://dx.doi.org/10.1016/j.hydroa.2019.100049
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