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Leveraging GCM-based forecasts for enhanced seasonal streamflow prediction in diverse hydrological regimes
Lopez, M. Girons
SMHI, Research Department, Hydrology.
Bosshard, Thomas
SMHI, Research Department, Hydrology.
Crochemore, Louise
SMHI, Research Department, Hydrology.
ORCID iD:
0000-0001-5776-6275
Pechlivanidis, Ilias
SMHI, Research Department, Hydrology.
ORCID iD:
0000-0002-3416-317X
2025 (English)
In:
Journal of Hydrology, ISSN 0022-1694, E-ISSN 1879-2707, Vol. 650, article id 132504
Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2025. Vol. 650, article id 132504
National Category
Oceanography, Hydrology and Water Resources
Research subject
Hydrology
Identifiers
URN:
urn:nbn:se:smhi:diva-6697
DOI:
10.1016/j.jhydrol.2024.132504
ISI:
001388031100001
OAI: oai:DiVA.org:smhi-6697
DiVA, id:
diva2:1924699
Funder
EU, Horizon 2020, 101037293
EU, Horizon Europe, 101121192
EU, Horizon 2020, 101003876
Swedish Energy Agency, 52095-1
Available from:
2025-01-07
Created:
2025-01-07
Last updated:
2025-06-12
Bibliographically approved
Open Access in DiVA
Leveraging GCM-based forecasts for enhanced seasonal streamflow prediction in diverse hydrological regimes
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70 downloads
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Bosshard, Thomas
Crochemore, Louise
Pechlivanidis, Ilias
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Lopez, M. Girons
Bosshard, Thomas
Crochemore, Louise
Pechlivanidis, Ilias
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Direct link
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Cite
Citation style
apa
ieee
modern-language-association-8th-edition
vancouver
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apa
ieee
modern-language-association-8th-edition
vancouver
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More styles
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de-DE
en-GB
en-US
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nn-NB
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