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This article reviews major impacts of climate change on agriculture and forestry.

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Abstract:A correct identification of drought events over vegetated lands can be achieved by detecting those soil moisture conditions that are both unusually dry compared with the 'normal' state and causing severe water stress to the vegetation. In this paper, we propose a novel drought index that accounts for the mutual occurrence of these two conditions by means of a multiplicative approach of a water deficit factor and a dryness probability factor. The former quantifies the actual level of plant water stress, whereas the latter verifies that the current water deficit condition is unusual for the specific site and period. The methodology was tested over Europe between 1995 and 2012 using soil moisture maps simulated by Lisflood, a distributed hydrological precipitation-runoff model. The proposed drought severity index (DSI) demonstrates to be able to detect the main drought events observed over Europe in the last two decades, as well as to provide a reasonable estimation of both extension and magnitude of these events. It also displays an improved adaptability to the range of possible conditions encountered in the experiment as compared with currently available indices based on the sole magnitude or frequency. The results show that, for the analyzed period, the most extended drought events observed over Europe were the ones in Central Europe in

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