This study aims to estimate hydrological drought risk using probabilistic analysis of bivariate drought characteristics to assess both past and future drought severity and duration in three basins located in the widest karst massif of northern Algeria. The procedures entail: (1) identification of extent of meteorological drought that could trigger corresponding hydrological drought through their characteristics; (2) assessment of future risk of extreme drought according to two emission scenarios of the representative concentration pathway (RCP 4.5 and 8.5); and (3) estimation of drought return periods using bivariate frequency analysis and investigation of their future change rates under climate change. Hydrological droughts were computed by using the bias-corrected future climate projections from nine global climate models downscaled using the Rossby Centre Regional Climate model (RCA4), and GR2M hydrological model. The analysis revealed a connection between meteorological and hydrological droughts occurrences and the response time depends on the memory effect of the considered basin. We also found strong consensus between past drought events return periods, determined by bivariate frequency analysis, and those determined by climate models under RCP8.5 scenario. Finally, in regards to drought return periods (10, 50 and 100-years), the risk of extreme drought recurrence in the future has been projected to be larger than the reference period.

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Abstract. In last decades, the impact of climate change started to appear in the semi-arid regions of the Mediterranean Basin. The severity and frequency of drought events in Northwestern Algeria have affected water resources availability and agriculture. This study aims to evaluate the temporal evolution of drought events characteristics, such as drought duration, frequency and severity, of the Beni Bahdel Dam catchment, Northwestern Algeria. Drought characteristics have been derived from the Standardized precipitation index (SPI) computed for the period from 1941 to 2100 using precipitation data from observations and simulations of the regional climate model RCA4 (Rossby Centre Atmosphere model, version 4). The RCA4 model was forced by the global circulation model MPI-ESM-LR under two Representative Concentration Pathways (RCPs) scenarios. The ability of the model simulations was firstly assessed to reproduce the drought characteristics from observed data (1951–2005). Then, future changes in drought characteristics over the twenty-first century were investigated under the two scenarios (RCP4.5 and RCP8.5). Results show an amplification of drought frequencies and durations in the future under the RCP8.5 scenario.

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<p>The Adige river basin (~11000 square kilometers) is the second longest in Italy and affects the population living in the Trentino-Alto Adige and Veneto region. It is an example of hydrological complex river basin because it includes high anthropization causing intensive and often conflicting water uses, presence of seasonal snow cover with runoff delayed from snow falling season to late Spring and Summer, glaciers, and irrigated areas, which are important for food production of the region.</p> <p>In this work, we model the hydrological cycle of the Adige river basin over the period 1980-2022, investigating the effect of three evapotranspiration formulations on the long term trends of each hydrological compartments, i.e. soil moisture, groundwater storage, and river runoff. The modeling part is implemented by exploiting the potential of the open-source, semi-distributed, component-based hydrological modeling system GEOframe modeling system, which is applied at daily time-step and at a high spatial resolution (<5 km²).</p> <p>The model, together with the different evapotranspiration formulations, has been validated against river runoff and satellite retrieved soil moisture data. Results, which have been analyzed also in the context of the 2022 drought which hit Northern Italy, show that increasing the complexity of the evapotranspiration formulation improved model performances for all the simulated hydrological components.</p>