CAMELS-CH - Building a Common Open Database for Catchments in Switzerland

Over recent years, numerous open catchment datasets have been published. In 2017, the first CAMELS (catchment attributes and meteorology for large-sample studies) dataset was released for the continental US by Addor et al. (2017). It comprises data for several hundreds of catchments including dynamic time series of daily resolution over several decades for discharge, precipitation and temperature - originally compiled by Newman et al. (2015) - as well as static basin attributes such as indices on topography, soil, geology and climate. Subsequently, similar datasets for several other countries were made or will be made publicly available. Some of these also contain additional data such as attributes on glaciers or human influence like, e.g., the CAMELS datasets for Chile (Alvarez-Garreton et al., 2018) and Great Britain (Coxon et al., 2020). Such datasets build an accessible and unified basis for reproducible and complementary research.  They led to a high stimulation of hydrological research with methodologies that could not be applied before, like the joint evaluation of a large number of catchments.

We present CAMELS-CH, a new dataset for about 200 basins in Switzerland that will be released in 2022. In this collaborative project, several academic institutions and agencies work together to publish a hydro-meteorological dataset that covers both dynamic and static catchment data, and that accounts for the wide range of hydrological regimes in Switzerland, e.g., alpine environment, hydropower usage, densely populated and cultivated regions, etc. We summarize the current state of the project, remaining challenges, in particular regarding translating base data into the CAMELS format, and the final steps toward dataset publication.

 

References

Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies. Hydrology and Earth System Sciences, 21, 5293-5313, 2017

Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Cortes, G., Garreaud, R., McPhee, J., Ayala, A.: The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies-Chile dataset, Hydrology and Earth System Sciences, 22, 5817–5846, 2018

Coxon, G., Addor, N., Bloomfield, J., Freer, J., Fry, M., Hannaford, J., Howden, N., Lane, R., Lewis, M., Robinson, E., Wagener, T.,and Woods, R.: CAMELS-GB: Hydrometeorological time series and landscape attributes for 671 catchments in Great Britain, Earth System Science Data 12, 2459–2483, 2020

Newman, A., Clark, M., Sampson, K., Wood, A., Hay, L., Bock, A., Viger, R., Blodgett, D., Brekke, L., Arnold, J.: Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance. Hydrology and Earth System Sciences, 19, 209-223, 2015