Explore Water

SMHI runs a number of large-scale HYPE models in addition to the Swedish version of HYPE. Each models produce water variables for the past, present and future. The results are used in operational forecast, several climate-change impact assessments and scientific research. We are happy to share the results from these models and water assessments with anyone who finds them useful. All data you can explore here is shared under license the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).

Explore by geographical domains

The model calculates water volume and fluxes over large geographical areas, which encompass many river basins, cross regional and international boundaries, and a number of different geophysical and climatic zones. Each river basin cover numerous coupled catchments and has thus a relatively high spatial resolution, although most basins are ungauged. The temporal resolution in the calculations is normally daily.

World

Europe

Arctic

Niger

La Plata

India

Explore by time periods

Explore visualisations of various hydrological variables and see how they vary in time and space for each region.

Historical Data

Watch long-term means and download time-series of various water variables at specific sites! Historical data is important to understand the character and natural variability of water resources, so that both societal and environmental concerns can be planned accordingly.

Forecast Data

Find current critical areas and provide time-series of water related variables at specific sites! Hydrological forecasts are used by many societal sectors: instance warning services, farmers and reservoir managers to decide on water storage or release.

Climate Change Data

Browse through the future state of water resources! On-going climate change will change both flow dynamics and availability of water resources on Planet Earth. We can prepare society so that actions can be taken to adapt to the new conditions expected.

Explore the data quality

Models are trying to simulate the real world based on numerical equations and simplified descriptions of the landscape. By definition, all models are wrong but can still be useful if they are close enough to reality.

Our Model Performance