There is a strong scientific debate on how drought will evolve under future climate change. Climate model outputs project an increase in drought frequency and severity by the end of the 21st century. However, there is a large uncertainty related to the extent of the global land area that will be impacted by enhanced climatological and hydrological droughts. Although climate metrics suggest a likely strong increase in future drought severity, hydrologic metrics do not show a similar signal. In the literature, numerous attempts have been made to explain these differences using several physical mechanisms. This study provides evidence that characterization of drought from different statistical perspectives can lead to unreliable detection of climatological/hydrological droughts in model projections and accordingly give a “false alarm” of the impacts of future climate change. In particular, this study analyses future projections based on different drought metrics and stresses that detecting trends in drought behavior in future projections must consider the extreme character of drought events by comparing the percentage change in drought magnitude relative to a reference climatological period and rely on the frequency of events in the tail of the distribution. In addition, the autoregressive character of drought indices makes necessary the use of the same temporal scale when comparing different drought metrics in order to maintain comparability. Taking into consideration all these factors, our study demonstrates that climatological and hydrological drought trends are likely to undergo similar temporal evolution during the 21st century, with almost 30% of the global land areas experiencing water deficit under future greenhouse gas emissions scenarios. As such, a proper characterization of drought using comparable metrics can introduce lower differences and more consistent outputs for future climatic and hydrologic droughts.

Attribution of trends in streamflow is complex, but essential, in identifying optimal management options for water resources. Disagreement remains on the relative role of climate change and human factors, including water abstractions and land cover change, in driving change in annual streamflow. We construct a very dense network of gauging stations (n = 1,874) from Ireland, the United Kingdom, France, Spain, and Portugal for the period of 1961–2012 to detect and then attribute changes in annual streamflow. Using regression‐based techniques, we show that climate (precipitation and atmospheric evaporative demand) explains many of the observed trends in northwest Europe, while for southwest Europe human disturbances better explain both temporal and spatial trends. For the latter, large increases in irrigated areas, agricultural intensification, and natural revegetation of marginal lands are inferred to be the dominant drivers of decreases in streamflow.

We analysed long-term variability and trends in meteorological droughts across Western Europe using the Standardized Precipitation Index (SPI). Precipitation data from 199 stations spanning the period 1851-2018 were employed, following homogenisation, to derive SPI-3 and SPI-12 series for each station, together with indices on drought duration and severity. Results reveal a general absence of statistically significant long-term trends in the study domain, with the exception of significant trends at some stations, generally covering short periods. The largest decreasing trends in SPI-3 (i.e., increasing drought conditions) were