Articles | Volume 18, issue 7
https://doi.org/10.5194/essd-18-4745-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-4745-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
09 Jul 2026
Data description article |
| 09 Jul 2026
| 09 Jul 2026
CAMELS-FI: hydrometeorological time series and landscape properties for 320 catchments in Finland
Department of geography and geology, University of Turku, Turku, 20014 Finland
Carlos Gonzales Inca
Department of geography and geology, University of Turku, Turku, 20014 Finland
Jari Uusikivi
Marine and freshwater solutions, Finnish Environment Institute, Helsinki, Finland
Petteri Alho
Department of geography and geology, University of Turku, Turku, 20014 Finland
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This study shows that climate-driven changes in spring flood patterns, especially hydrograph shape and peak sequencing, strongly affect sediment transport and river morphology in a subarctic river. Rising temperatures and more rain-on-snow events are increasing flood variability, leading to more event-driven and unpredictable sediment dynamics. Adaptive management is needed to respond to these emerging changes.
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Communities all around the Arctic urgently need information on how their coast is changing in response to climate change. We developed an automized method for mapping Arctic shoreline displacement from open satellite images. We show how coastal change hotspots, glacier retreat, spit migration and delta development can be identified from such data. Being highly efficient and accurate, our method has potential for calculating the first 40-year time series of shoreline displacement in the Arctic.
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Short summary
This study introduces CAMELS-FI (Catchment Attributes and MEteorology for Large-sample Studies-Finland), an extensive, consistent, high quality and easily usable hydro-meteorological dataset for 320 catchments in Finland. For each catchment, it includes daily streamflow data of up to 63 years (1961–2023) at the pour point of the catchment, daily catchment averaged meteorology for 14 variables for the full 63 years and 85 “static” attributes describing metadata of the stream gauges and the catchments, biogeophysical and societal attributes.
This study introduces CAMELS-FI (Catchment Attributes and MEteorology for Large-sample...
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