Natural and human influences on the link between meteorological and hydrological drought indices for a large set of catchments in the contiguous United States

Precipitation‐based drought indices are most commonly used in drought monitoring and early warning systems whereas impacts of drought are often related to other domains of the hydrological cycle such as streamflow. Precipitation droughts do not always coincide with streamflow droughts, as the propagation from precipitation to streamflow is affected by climate, catchment properties and human influences. For monitoring in ungauged catchments it is the question to what extent drought indices solely based on precipitation or other (more recently developed) meteorological drought indices that include evaporation or snowmelt, have a stronger correlation with streamflow and whether this correlation is weaker in catchments where streamflow is altered by human influences. Results of a correlation exercise between various meteorological drought indices and streamflow showed that the strongest correlation was often found for meteorological drought indices that include evaporation (especially in drier climates) or snow processes (especially in colder climates). Most catchments with an indicated presence of human influences showed a maximum correlation between meteorological drought indices and streamflow that was comparable in strength to the same correlation for catchments with near‐natural flow. However, up to 15% of catchments with human‐influenced streamflow records show weaker correlations. Drought indices derived from these influenced records with a weaker correlation do not necessarily correspond to reported drought impacts. In conclusion, knowing which meteorological drought index has the strongest correlation with streamflow in different climate zones has the potential of improving large‐scale drought monitoring and early warning systems in ungauged areas or regions that lack real‐time streamflow availability

Bioclimatic analysis in a region of southern Italy (Calabria)

In this study, an analysis of precipitation and temperature data has been performed over 67 series observed in a region of southern Italy (Calabria). At first, to detect possible trends in the time series, an analysis was performed with the Mann–Kendall non-parametric test applied at monthly and seasonal scale. An additional investigation, useful for checking the climate change effects on vegetation, has also been included analysing bioclimatic indicators. In particular, Emberger, Rivas-Martinez and De Martonne indices were calculated by using monthly temperature and precipitation data in the period 1916–2010. The spatial pattern of the indices has been evaluated and, in order to link the vegetation and the indices,different indices maps have been intersected with the land cover data, given by the Corine Land Cover map. Moreover, the temporal evolution of the indices and of the vegetation has been analysed. Results suggest that climate change may be responsible for the forest cover change, but, given also the good relationship between the various types of bioclimate and forest formations, human activities must be considered