Early 21st-century droughts in Europe have been broadly regarded as exceptionally severe, substantially affecting a wide range of socio-economic sectors. These extreme events were linked mainly to increases in temperature and record-breaking heatwaves that have been influencing Europe since 2000, in combination with a lack of precipitation during the summer months. Drought propagated through all respective compartments of the hydrological cycle, involving low runoff and prolonged soil moisture deficits. What if these recent droughts are not as extreme as previously thought? Using reconstructed droughts over the last 250 years, we show that although the 2003 and 2015 droughts may be regarded as the most extreme droughts driven by precipitation deficits during the vegetation period, their spatial extent and severity at a long-term European scale are less uncommon. This conclusion is evident in our concurrent investigation of three major drought types – meteorological (precipitation), agricultural (soil moisture) and hydrological (grid-scale runoff) droughts. Additionally, unprecedented drying trends for soil moisture and corresponding increases in the frequency of agricultural droughts are also observed, reflecting the recurring periods of high temperatures. Since intense and extended meteorological droughts may reemerge in the future, our study highlights concerns regarding the impacts of such extreme events when combined with persistent decrease in European soil moisture.

In the last decades, the impactful European warm-season droughts have been steadily increasing, substituting other drought types.

In recent years, there has been growing concern about the effect of global warming on water resources, especially at regional and continental scales. The last IPCC report on extremes states that there is medium confidence about an increase on European drought frequency during twentieth century. Here we use the Old World Drought Atlas palaeoclimatic reconstruction to show that when Europe’s hydroclimate is examined under a millennial, multi-scale perspective, a significant decrease in dryness can be observed since 1920 over most of central and northern Europe. On the contrary, in the south, drying conditions have prevailed, creating an intense north-to-south dipole. In both cases, hydroclimatic conditions have shifted to, and in some regions exceeded, their millennial boundaries, remaining at these extreme levels for the longest period of the 1000-year-long record.

The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI) and the standardized precipitation evaporation index (SPEI) and were derived for the period of 1948–2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons.

A Multi-Model Assessment of Climate Change Impact on Hydrological Regime in the Czech Republic: In present paper we assess the climate change impact on mean runoff between the periods 1961-1990 (control period) and 2070-2099 (scenario period) in the Czech Republic. Hydrological balance is modelled with a conceptual hydrological model BILAN at 250 catchments of different sizes and climatic conditions. Climate change scenarios are derived using simple delta approach, i.e. observed series of precipitation, temperature and relative air humidity are perturbed in order to give the same changes between the control and scenario period as in the ensemble of 15 transient regional climate model (RCM) simulations. The parameters of the hydrological model are for each catchment estimated using observed data. These parameters are subsequently used to derive discharge series under climate change conditions for each RCM simulation. Although the differences in the absolute values of the changes in runoff are considerable, robust patterns of changes can be identified. The majority of the scenarios project an increase in winter runoff in the northern part of the Czech Republic, especially at catchments with high elevation. The scenarios also agree on a decrease in spring and summer runoff in most of the catchments.