Merlo et al. (2026) Tracking shifts in European drought hotspots

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

Identification

• Journal: Environmental Research Letters
• Year: 2026
• Date: 2026-03-03
• Authors: Martina Merlo, Hans de Moel, Yiheng Du, Ilias Pechlivanidis, Andrea Castelletti
• DOI: 10.1088/1748-9326/ae4ca7

Research Groups

Not specified in the abstract.

Short Summary

This study develops novel impact-based Combined Drought Indices (iCDIs) using a machine learning framework to directly link hydroclimatic drivers to remotely sensed vegetation stress across Europe. The iCDIs outperform traditional indices and project a significant northward shift in future drought impacts, identifying Central Europe as an emerging hotspot, contrary to conventional views.

Objective

• To develop novel impact-based Combined Drought Indices (iCDIs) that directly relate hydroclimatic drivers (precipitation, temperature, soil moisture) to remotely sensed vegetation stress, serving as a proxy for agricultural impacts, to better capture drought hazards.

Study Configuration

• Spatial Scale: European domain, specifically across distinct hydrological clusters and river basins, with focus on Central Europe and Mediterranean regions.
• Temporal Scale: Current observed vegetation responses and future projections under warming scenarios.

Methodology and Data

• Models used: Machine learning framework for optimizing predictor selection and developing iCDIs.
• Data sources: Remotely sensed vegetation stress (as a proxy for agricultural impacts), and hydroclimatic predictors including precipitation, temperature, and soil moisture.

Main Results

• The developed impact-based Combined Drought Indices (iCDIs) using a bottom-up machine learning approach outperform traditional indices in reproducing observed vegetation responses across European river basins.
• Future projections of iCDIs under warming scenarios reveal a distinct northward shift in drought impacts.
• Central Europe is identified as an increasingly vulnerable hotspot for future drought impacts.
• This projected spatial reconfiguration of risk contrasts with patterns suggested by standardised indices, which typically emphasize Mediterranean regions as primary areas of concern.

Contributions

• Introduction of novel impact-based Combined Drought Indices (iCDIs) that directly link hydroclimatic drivers to observed vegetation stress using a machine learning framework.
• Demonstration of superior performance of iCDIs over traditional indices in capturing actual vegetation responses to drought.
• Identification of a critical northward shift in future drought impacts across Europe, highlighting Central Europe as an emerging hotspot, which challenges existing understanding based on standardized indices.
• Underscoring the urgency and value of adopting impact-oriented drought diagnostics for more effective climate-resilient planning and adaptive risk governance.

Funding

Not specified in the abstract.

Citation

@article{Merlo2026Tracking,
  author = {Merlo, Martina and Moel, Hans de and Du, Yiheng and Pechlivanidis, Ilias and Castelletti, Andrea},
  title = {Tracking shifts in European drought hotspots},
  journal = {Environmental Research Letters},
  year = {2026},
  doi = {10.1088/1748-9326/ae4ca7},
  url = {https://doi.org/10.1088/1748-9326/ae4ca7}
}