Janzing et al. (2026) Spatiotemporal Dynamics of Streamflow Drought in the Larger Alpine Region

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Repository for Publications and Research Data (ETH Zurich)
• Year: 2026
• Date: 2026-03-01
• Authors: Joren Janzing, Niko Wanders, Marit Van Tiel, Manuela Brunner
• DOI: 10.3929/ethz-c-000797007

Research Groups

The provided text does not explicitly list the main research groups, labs, or departments involved in the study.

Short Summary

This study analyzes the spatiotemporal dynamics of streamflow droughts across the larger Alpine region using high-resolution hydrological model simulations and a novel clustering algorithm, revealing that extensive droughts exhibit growth and recovery phases, regional differences in behavior, and are primarily driven by rainfall deficits, though often by multiple interacting processes.

Objective

• To analyze the spatiotemporal dynamics of streamflow drought events over the larger Alpine region.

Study Configuration

• Spatial Scale: Larger Alpine region, including both mountain and surrounding lowland river networks.
• Temporal Scale: Analysis of streamflow drought evolution over time; specific duration not provided in the text.

Methodology and Data

• Models used: PCR-GLOBWB2.0 (hydrological model), novel spatial and temporal clustering algorithm.
• Data sources: High-resolution simulations from the hydrological model PCR-GLOBWB2.0.

Main Results

• Spatially-extensive streamflow droughts (≥ 500 km of river network) typically experience phases of growth and recovery, sometimes consisting of several spatially-distinct sub-events.
• Streamflow drought behavior differs across geographic regions, with the Alpine mountain range often limiting drought extent.
• The mountain river network is less frequently part of spatially-extensive drought events compared to surrounding lowland rivers.
• The spatial evolution of streamflow drought is influenced by various hydrometeorological drivers.
• Rainfall deficits are identified as the most dominant driver of spatially-extensive streamflow droughts in the study domain.
• Many drought events result from the interplay of multiple processes, and the dominant drivers can change over time as the affected domain evolves.

Contributions

• Provides a detailed spatiotemporal analysis of streamflow droughts over the larger Alpine region, moving beyond spatially limited studies.
• Introduces and applies a novel spatial and temporal clustering algorithm to track drought events.
• Highlights the complex dynamics of extensive droughts, including growth/recovery phases and regional differences in behavior.
• Identifies dominant hydrometeorological drivers and their temporal variability, offering insights for future water management and drought impact mitigation strategies.

Funding

The provided text does not contain information regarding the funding projects, programs, or reference codes for this research.

Citation

@article{Janzing2026Spatiotemporal,
  author = {Janzing, Joren and Wanders, Niko and Tiel, Marit Van and Brunner, Manuela},
  title = {Spatiotemporal Dynamics of Streamflow Drought in the Larger Alpine Region},
  journal = {Repository for Publications and Research Data (ETH Zurich)},
  year = {2026},
  doi = {10.3929/ethz-c-000797007},
  url = {https://doi.org/10.3929/ethz-c-000797007}
}