Drought impact information is important for risk assessment. But, there is little consensus on impact data monitoring. The European Drought Impacts Database (EDID) combines several existing text-based datasets with the results from new searches for impact information into a structured database with spatial and temporal attributes. Allowing research as well as operational use, its contents show where and when in Europe drought has affected agriculture, water supply, ecosystems, and other sectors.

This study introduces a new metric for hydrological model calibration combining traditional model efficiency measures with a new component to better assess similarity between observed and simulated river flows. Tests on two hydrological models and large catchment samples show improved low-flow simulations without degrading high-flow accuracy. The new metric can support more reliable modeling for droughts and floods and is already being adopted in operational monitoring and forecasting systems.

A computationally inexpensive climate model analog method yields skillful climate predictions across timescales, from seasons to multiple years, complementing existing climate prediction systems and potentially providing valuable information for sectors like agriculture and energy.

Our global review of 130 000 peer-reviewed articles reveals that drought forecasting and plant genetics dominate drought research priorities. Using topic modelling, we traced evolving themes from 1901 to 2022, highlighting a shift from ecology to cutting-edge technologies. By applying unsupervised machine learning, we offer insights into how integrated approaches matter, guiding future priorities to strengthen drought resilience and to safeguard water resources.

Precipitation and soil moisture have the potential to be jointly used for the modeling of drought conditions. In this research, we analysed how their statistical inter-relationship varies across Europe. We found some clear spatial patterns, especially in the so-called tail dependence (which measures the strength of the relationship for the extreme values). The results suggest that the tail dependence needs to be accounted for to correctly assess the value of joint modeling for drought.