André Almagro, Paulo Tarso S. Oliveira, André S. Ballarin
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SSP-CABra—Streamflow Scenarios Projections for Brazilian Catchments
Climate change has significant impacts on hydrological fluxes worldwide, with pronounced effects in Brazil, including intense and recurrent droughts and floods. Accurate streamflow prediction is therefore essential for advancing water resources engineering, improving water resources management, and informing climate adaptation strategies. Here, we introduce the Streamflow Scenarios Projections for Brazilian Catchments (SSP-CABra), which provides long-term to daily streamflow simulations for 735 Brazilian catchments. These simulations are generated using five hydrological models of varying complexity, forced by 10 bias-corrected CMIP6-based climate simulations for historical (1980–2013) and future (2015–2100; SSP2-4.5 and SSP5-8.5) periods. SSP-CABra addresses a critical gap in large-scale hydrological modelling for Brazil, offering valuable insights for researchers and policymakers. Despite its broad applicability, the dataset includes models with varying performance across regions; users should assess model skill locally to ensure appropriate use, particularly for decision-making or extreme event analyses. Still, by leveraging multiple models and climate scenarios, SSP-CABra supports not only the mitigation of climate change impacts on water security, but also advances the understanding of model performance and regional hydrological behaviour.
Geoscience Data JournalGEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍:
Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered.
An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices.
Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.