Articles | Volume 17, issue 2
https://doi.org/10.5194/essd-17-703-2025
https://doi.org/10.5194/essd-17-703-2025
Data description paper
 | 
21 Feb 2025
Data description paper |  | 21 Feb 2025

High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland

Jan Magnusson, Yves Bühler, Louis Quéno, Bertrand Cluzet, Giulia Mazzotti, Clare Webster, Rebecca Mott, and Tobias Jonas

Related authors

Exploring how Sentinel-1 wet-snow maps can inform fully distributed physically based snowpack models
Bertrand Cluzet, Jan Magnusson, Louis Quéno, Giulia Mazzotti, Rebecca Mott, and Tobias Jonas
The Cryosphere, 18, 5753–5767, https://doi.org/10.5194/tc-18-5753-2024,https://doi.org/10.5194/tc-18-5753-2024, 2024
Short summary

Related subject area

Domain: ESSD – Land | Subject: Hydrology
GRILSS: opening the gateway to global reservoir sedimentation data curation
Sanchit Minocha and Faisal Hossain
Earth Syst. Sci. Data, 17, 1743–1759, https://doi.org/10.5194/essd-17-1743-2025,https://doi.org/10.5194/essd-17-1743-2025, 2025
Short summary
A worldwide event-based debris flow barrier dam dataset from 1800 to 2023
Haiguang Cheng, Kaiheng Hu, Shuang Liu, Xiaopeng Zhang, Hao Li, Qiyuan Zhang, Lan Ning, Manish Raj Gouli, Pu Li, Anna Yang, Peng Zhao, Junyu Liu, and Li Wei
Earth Syst. Sci. Data, 17, 1573–1593, https://doi.org/10.5194/essd-17-1573-2025,https://doi.org/10.5194/essd-17-1573-2025, 2025
Short summary
CAMELS-DK: hydrometeorological time series and landscape attributes for 3330 Danish catchments with streamflow observations from 304 gauged stations
Jun Liu, Julian Koch, Simon Stisen, Lars Troldborg, Anker Lajer Højberg, Hans Thodsen, Mark F. T. Hansen, and Raphael J. M. Schneider
Earth Syst. Sci. Data, 17, 1551–1572, https://doi.org/10.5194/essd-17-1551-2025,https://doi.org/10.5194/essd-17-1551-2025, 2025
Short summary
An in situ daily dataset for benchmarking temporal variability of groundwater recharge
Pragnaditya Malakar, Aatish Anshuman, Mukesh Kumar, Georgios Boumis, T. Prabhakar Clement, Arik Tashie, Hitesh Thakur, Nagaraj Bhat, and Lokendra Rathore
Earth Syst. Sci. Data, 17, 1515–1528, https://doi.org/10.5194/essd-17-1515-2025,https://doi.org/10.5194/essd-17-1515-2025, 2025
Short summary
CAMELS-FR dataset: a large-sample hydroclimatic dataset for France to explore hydrological diversity and support model benchmarking
Olivier Delaigue, Guilherme Mendoza Guimarães, Pierre Brigode, Benoît Génot, Charles Perrin, Jean-Michel Soubeyroux, Bruno Janet, Nans Addor, and Vazken Andréassian
Earth Syst. Sci. Data, 17, 1461–1479, https://doi.org/10.5194/essd-17-1461-2025,https://doi.org/10.5194/essd-17-1461-2025, 2025
Short summary

Cited articles

Avanzi, F., Munerol, F., Milelli, M., Gabellani, S., Massari, C., Girotto, M., Cremonese, E., Galvagno, M., Bruno, G., di Cella, U. M., Rossi, L., Altamura, M., and Ferraris, L.: Winter snow deficit was a harbinger of summer 2022 socio-hydrologic drought in the Po Basin, Italy, Commun. Earth Environ., 5, 64, https://doi.org/10.1038/s43247-024-01222-z, 2024. 
Baggi, S. and Schweizer, J.: Characteristics of wet-snow avalanche activity: 20 years of observations from a high alpine valley (Dischma, Switzerland), Nat. Hazards, 50, 97–108, https://doi.org/10.1007/s11069-008-9322-7, 2009. 
Barton, Y., Sideris, I. V., Raupach, T. H., Gabella, M., Germann, U., and Martius, O.: A multi-year assessment of sub-hourly gridded precipitation for Switzerland based on a blended radar—Rain-gauge dataset, Int. J. Climatol., 40, 5208–5222, https://doi.org/10.1002/joc.6514, 2020. 
Bavay, M., Lehning, M., Jonas, T., and Löwe, H.: Simulations of future snow cover and discharge in Alpine headwater catchments, Hydrol. Process., 23, 95–108, https://doi.org/10.1002/hyp.7195, 2009. 
Bavay, M., Grünewald, T., and Lehning, M.: Response of snow cover and runoff to climate change in high Alpine catchments of Eastern Switzerland, Adv. Water Resour., 55, 4–16, https://doi.org/10.1016/j.advwatres.2012.12.009, 2013. 
Download
Short summary
In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land surface, and hydrological models, with potential applications in similar high-alpine catchments.
Share
Altmetrics
Final-revised paper
Preprint