Matt et al. (2025) HYD-RESPONSES: daily hydro-meteorological catchment-level time series to analyse HYDrological drought dynamics in RESPONSE to (cumulative) water deficits in Swiss catchments

Identification

• Journal: Open Access CRIS of the University of Bern
• Year: 2025
• Date: 2025-10-06
• Authors: Christoph von Matt, Benjamin D. Stocker, Olivia Martius
• DOI: 10.48620/94341

Research Groups

• Geographisches Institut (GIUB) - Klimafolgenforschung, University of Bern
• Oeschger Centre for Climate Change Research (OCCR), University of Bern
• Institute of Geography, Geocomputation and Earth Observation, University of Bern
• Oeschger Centre for Climate Change Research (OCCR) - MobiLab, University of Bern

Short Summary

This paper introduces the HYD-RESPONSES dataset, providing new daily hydro-meteorological time series and drought indicators for 184 Swiss catchments to facilitate the analysis of hydrological drought dynamics and their responses to cumulative water deficits. The dataset supports process studies, statistical analyses, and the training of machine learning models for improved drought understanding and warning applications.

Objective

• To provide a comprehensive daily catchment-level hydro-meteorological dataset for 184 Swiss catchments to enable detailed analysis of hydrological drought dynamics, propagation, and catchment responses to water deficits.

Study Configuration

• Spatial Scale: 184 small to large catchments across Switzerland, covering diverse streamflow regimes, altitudes, biogeographic regions, and anthropogenic influences.
• Temporal Scale: Daily time series for hydro-meteorological variables and derived indicators; standardized indices provided on aggregation scales from 1 to 24 months; climatology and anomalies available daily, monthly, seasonally, and yearly.

Methodology and Data

• Models used:
  • Standardized drought indices: Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SMRI).
  • Non-standardized drought indices: Cumulative Water Deficit (CWD), Potential Cumulative Water Deficit (PCWD), Cumulative Streamflow Deficit (CQD).
  • Drought event identification: Two percentile-based event definitions (fixed and variable threshold).
• Data sources:
  • Streamflow: Daily average measurements from the Federal Office for the Environment (FOEN) surface water monitoring network.
  • Hydro-meteorological data (precipitation, temperature, radiation, snow, soil moisture): Spatially gridded data from MeteoSwiss (RhiresD, TabsD, TmaxD, TminD, SrelD), MeteoSwiss and WSL Institute for Snow and Avalanche Research SLF (SPASS), SLF (OSHD), and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5-Land reanalysis.
  • Catchment descriptors: Hydro-climatological, hydro-terrestrial, and streamflow characteristics.

Main Results

• The HYD-RESPONSES dataset provides daily time series for key hydro-meteorological variables (precipitation, snow water equivalent, temperature, soil moisture, potential evaporation, streamflow) for 184 Swiss catchments.
• It includes derived indicators related to snowfall, snowmelt, water balance, and streamflow.
• The dataset offers standardized (SPI, SPEI, SMRI) and non-standardized (CWD, PCWD, CQD) drought indices on multiple aggregation scales (1 to 24 months).
• Climatology and standardized anomalies are available for all variables and indices on daily, monthly, seasonal, and yearly time scales.
• Drought event time series, including event numbers and durations, are provided for streamflow droughts and cumulative water deficits.
• Detailed catchment descriptors are included, covering hydro-climatological, hydro-terrestrial, and streamflow characteristics.

Contributions

• Provides a novel, comprehensive, and high-resolution daily catchment-level hydro-meteorological dataset specifically tailored for studying hydrological drought dynamics in Switzerland.
• Enables diverse research applications, including the study of weather-driven streamflow extremes, training of data-driven machine learning algorithms, analysis of drought propagation, and comparative studies of catchment responses.
• Offers a valuable resource for improving the understanding of low flow conditions, supporting warning applications, and informing infrastructure planning in Switzerland.
• The dataset is compatible with existing resources like the CAMELS-CH dataset, enhancing its utility for comparative hydrological studies.

Funding

• Federal Office for the Environment (FOEN) / Bundesamt für Umwelt (BAFU)

Citation

@article{Matt2025HYDRESPONSES,
  author = {Matt, Christoph von and Stocker, Benjamin D. and Martius, Olivia},
  title = {HYD-RESPONSES: daily hydro-meteorological catchment-level time series to analyse HYDrological drought dynamics in RESPONSE to (cumulative) water deficits in Swiss catchments},
  journal = {Open Access CRIS of the University of Bern},
  year = {2025},
  doi = {10.48620/94341},
  url = {https://doi.org/10.48620/94341}
}