The Hydrological Predictions for the Environment (HYPE) model is a semi-distributed, physically based hydrological model, which simulates water flow and substances on their way from precipitation through different storage compartments and fluxes to the sea (Lindström et al., 2010). The HYPE model was developed in the early 2000’s at SMHI, when introducing the EU Water Framework Directive (WFD) in Sweden. The aim was to provide water information to society for environmental and climate change assessments with high spatial resolution, also for ungauged conditions, making use of new technology and many different data sources. The model has since been set up all over the world and applied to both forecasting and climate projections.

The HYPE code (Lindström et al., 2010) is process based and distributed when describing hydrological processes in different sub basins, although the algorithms are not purely based on physical laws but of more conceptual nature. It is meant to be applied in a multi-basin manner to achieve high spatial distribution of flow paths in the landscape. It can be evaluated against point measurements in the river network and against spatially distributed observations, such as Earth Observations or interpolated products from in-situ monitoring.

Hype model
Schematic representation of the HYPE model processes.

Over time, the HYPE model has been applied globally (Arheimer et al., 2020) with evaluation in many different environments often resulting in further code development to address various hydro-climatic features, e.g. across Europe (Donnelly et al., 2026; Hundecha et al., 2016), the sub-continent of India (Pechlivanidis and Arheimer, 2015), in Africa (Andersson et al. 2017), the Arctic (MacDonald et al., 2017; Lebedeva and Gustafsson, 2021), Asia (Du et al., 2020) and Central America (Arciniega-Esparza et al,. 2022).

The HYPE model is currently used for forecasting, environmental assessments, water management and planning, climate change impact studies and scenario modelling. It is used operationally in the Warning Service of many countries and both code and model results are shared for Open Science at HYPEweb. The code is open source, well documented and accompanied with tutorials, guidance and regular training courses.


Andersson, J.C.M., Arheimer B., Traoré, F., Gustafsson, D., Ali, A. 2017. Process refinements improve a hydrological model concept applied to the Niger River basin. Hydrological Processes 31(25), pp.4540-4554.

Arciniega-Esparza, S., Birkel, C., Chavarría-Palma, A., Arheimer, B., and Breña-Naranjo, J. A., 2022. Remote sensing-aided rainfall–runoff modeling in the tropics of Costa Rica, Hydrol. Earth Syst. Sci., 26, 975–999,

Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J. C. M., Hasan, A., and Pineda, L., 2020. Global catchment modelling using World-Wide HYPE (WWH), open data and stepwise parameter estimation, Hydrol. Earth Syst. Sci. 24, 535–559,

Donnelly, C, Andersson, J.C.M. and Arheimer, B., 2016. Using flow signatures and catchment similarities to evaluate a multi-basin model (E-HYPE) across Europe. Hydr. Sciences Journal 61(2):255-273, doi: 10.1080/02626667.2015.1027710

Du, T.L.T., Lee, H., Bui, D.D., Arheimer, B., Li, H-Y., Olsson, J., Darby, S.E., Sheffield, J., Kim, D., and Hwang, E. 2020. Streamflow prediction in “geopolitically ungauged” basins using satellite observations and regionalization at subcontinental scale. Journal of Hydrology, ISSN: 0022-1694, Vol: 588, Page: 125016.

Hundecha, Y., Arheimer, B., Donnelly, C., Pechlivanidis, I. 2016. A regional parameter estimation scheme for a pan-European multi-basin model. Journal of Hydrology: Regional Studies, Volume 6, June 2016, Pages 90-111. doi:10.1016/j.ejrh.2016.04.002

Lebedeva, L., and Gustafsson, D. 2021. Streamflow Changes of Small and Large Rivers in the Aldan River Basin, Eastern Siberia. Water 13, no. 19: 2747.

Lindström, G., Pers, C.P., Rosberg, J., Strömqvist, J., and Arheimer, B. 2010. Development and test of the HYPE (Hydrological Predictions for the Environment) model – A water quality model for different spatial scales. Hydrology Research 41.3-4:295-319.

MacDonald, M. K., Stadnyk, T. A., Déry, S. J., Braun, M., Gustafsson, D., Isberg, K., and Arheimer, B. 2018. Impacts of 1.5 and 2.0 °C warming on pan-Arctic river discharge into the Hudson Bay Complex through 2070. Geophysical Research Letters, 45, 7561–7570. 

Pechlivanidis, I. G. and Arheimer, B. 2015. Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case, Hydrol. Earth Syst. Sci., 19, 4559-4579, doi:10.5194/hess-19-4559-2015.