A high-resolution snow and hydrometeorological dataset for the Dischma region in Switzerland

https://doi.org/10.5194/essd-17-703-2025

Description

This repository contains data from the alpine Dischma watershed and its surroundings in eastern Switzerland and includes: (a) hourly hydrometeorological data with 100m spatial resolution, (b) remotely sensed snow depth data with 100m spatial resolution obtained at peak of winter, and (c) station measurements of variables such as snow depth and catchment runoff.

This dataset is particularly suited for (a) different simulation experiments using distributed and process-based models, including physics-based snow and hydrological models, (b) testing various snow data assimilation schemes, and (c) developing models representing snow-forest interactions.

The dataset is described in detail in:

Magnusson, J., Bühler, Y., Quéno, L., Cluzet, B., Mazzotti, G., Webster, C., Mott, R., and Jonas, T.: High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2024-374 , in review, 2024.

We provide 7 water years of high-resolution (100 m) spatially distributed hourly meteorological data for the Dischma catchment and surrounding areas in eastern Switzerland that will be useful as input to various models. These model forcing data include air temperature, relative humidity, wind speed and direction, short- and longwave radiation, and precipitation, alongside land and forest cover information. The meteorological data were obtained from a numerical weather prediction model and precipitation radar product. The model forcing data, used by Quéno et al. (2024) for detailed snow simulations including snow redistribution processes, have been formatted for ease of use to facilitate different modelling experiments. We additionally provide forest structure data, based on a detailed canopy height model, enabling modelling of snow–forest interactions in heterogeneous landscapes, thus ensuring that the impact of forest cover is accurately captured in snow and hydrological applications.

In addition to the model input data, we have assembled validation datasets, including the following: (a) snow depth measurements from airborne lidar and photogrammetry surveys, quality-controlled and upscaled to a 100 m grid; (b) daily controlled and gap-filled snow depth recordings as well as biweekly snow water equivalent observations, both from ground locations; and (c) hourly runoff and stream temperature measurements at the basin outlet of the Dischma catchment. The lidar and photogrammetric surveys provide the most extensive spatial snow depth dataset in the European Alps, with comparable quality to the Airborne Snow Observatory in the USA (Painter et al., 2016) but covering a smaller area.

Overall, the dataset is valuable for enhancing physics-based snow, land surface, and hydrological models with applications in high-alpine catchments. This dataset is particularly useful for modelling snow redistribution through wind and avalanches, snow–forest interactions, and developing snow data assimilation schemes based on forcing data typically available in an operational setting. We anticipate that this dataset will lower the barriers for the snow and hydrological modelling communities to conduct simulation experiments in the Dischma region, a typical headwater catchment in the European Alps with a long history of diverse research studies.

Magnusson, J., Jonas, T., Bühler, Y., Webster, C., Mazzotti, G. (2024). A high-resolution snow and hydrometeorological dataset for the Dischma region in Switzerland. EnviDat. https://www.doi.org/10.16904/envidat.568 .

Creative Commons Attribution (CC-BY 4.0)

https://www.envidat.ch/#/metadata/inarch-dischma-dataset

The inarch_dischma_20241219.zip file contains data for the period from 2016 to 2023, as described in the publication linked to this repository. The inarch_dischma_20250821.zip file contains data for the period from 2023 to 2024, and thus ammends the previous file with an additional year of data. Both zip files contain a readme describing the content in detail. Static files (e.g., landuse data) are only available in the inarch_dischma_20241219.zip file. There is a short period of overlapping data in both files. The newest file contains the most up-to-date data. Data last updated 2025-08-21.