Floods are natural disasters that cause extreme economic damage and therefore have a significant impact on society. Understanding the spatial and temporal characteristics exhibited by floods is one of the crucial parts of effective flood management. The Danube River with its basin is an important region in Europe and floods have occurred in the Danube River basin throughout history. Flood frequency analysis (FFA) and seasonality analysis were performed in this study using the annual maximum discharge series data from 86 gauging stations in order to form a comprehensive characterisation of floods in the Danube River basin. The results of the study demonstrate that some noticeable clusters of stations can be identified based on the best-fitting distribution regarding FFA. Furthermore, the best-fitting distributions regarding FFA for the stations in the Danube River basin are generalized extreme values (GEV) and log Pearson type 3 (LP3) distributions as among 86 considered gauging stations, 76 stations have one of these two distributions among their two best fits. Moreover, seasonality analysis demonstrates that large floods in the Danube River basin mainly occur in the spring, and flood seasonality in the basin is highly clustered.

<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>

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Abstract. Heat waves (HW) and cold waves (CW) can have considerable impact on people. Mapping risks of extreme temperature at local scale accounting for the interactions between hazard, exposure and vulnerability remains a challenging task. In this study, we quantify human risks from HW and CW at high resolution for theTrentino-Alto Adige region of Italy from 1980 to 2018. We use the Heat Wave Magnitude Index daily (HWMId) and a Cold Wave Magnitude Index daily (CWMId) as temperature-based indicators and apply a Tweedie zero-inflated distribution to derive hazard intensities and frequencies. The hazard maps are combined with high-resolution maps of population, for which the vulnerability is quantified at community and city level using a set of eight socioeconomic indicators. We find a statistically significant increase in HW hazard and exposure, with 6.0-times more people exposed to extreme heat after 2000 compared to the last two decades of the previous century. CW hazard and exposure remained stagnant over the studied period in the region. We observe a general trend towards increased resilience to extreme temperature spells over the region. In the larger cities of the region, however, we find that vulnerability has increased due to an ageing population and more single households. HW risk has risen practically everywhere in the region, indicating that the reduction in vulnerability in the smaller communities is outpaced by the increase in HW hazard. In the large cities, HW risk levels in the 2010s are 50 % larger compared to the 1980s due to the rise in both hazard and vulnerability. Whereas in smaller communities, stagnant CW hazard and declining vulnerability results in reduced CW risk levels, the risk level in cities grew by 20 % due to the increased vulnerability over the study period. The findings of our study are highly relevant for steering investments in local risk mitigation measures, while the method can be applied to other regions that have detailed information on hazard, exposure and vulnerability indicators.

<p>River Adige is the second longest in Italy and affects the population living in the Trentino Alto Adige and the Venetian plain for irrigation. Having an area relatively small (~11000 square kilometers), it is however affected by a complexity of issues including: high anthropization causing intensive and often conflicting water uses, displacement of water resources from one sub-catchment to another, presence of seasonal snow cover with runoff delayed from snow falling season to late Spring and Summer, glaciers depletion under the climate change impulse. All those issues make the modeling of the water cycle of the river area challenging and, at the same time urgent.</p><p>This contribution has the objective to illustrate an effort to model the basin at high resolution with the aim to search for the closure of the water and energy budgets for the years of 1980-2018. Within this budgets simulation, we want to address a quantitative assessment of the effects of recent climate changes on the availability of the resource and, for what concern, the basin area evaluate the regional variability of the resource up to the scale of sub-catchments of area of around 5km². This is done with the help of the GEOframe modeling system (Formetta et al, 2014), an open-source, semi-distributed, component-based hydrological modeling system. The different components of the system enable to model different processes of the hydrological cycle: geomorphology, radiation, evapotranspiration, rainfall-snowmelt separation, discharge calculation and the try of different hypothesis on the work of the elementary hydrological components. The results are also compared with those of the analysis conducted in Thedoros et al., 2020.</p><p>References:</p><p>Formetta, G., A. Antonello, S. Franceschi, O. David, and R. Rigon. 2014. “Hydrological Modelling with Components: A GIS-Based Open-Source Framework.” <em>Environmental Modelling & Software</em> 55 (May): 190–200.</p><p>Mastrotheodoros, Theodoros, Christoforos Pappas, Peter Molnar, Paolo Burlando, Gabriele Manoli, Juraj Parajka, Riccardo Rigon, et al. 2020. “More Green and Less Blue Water in the Alps during Warmer Summers.” <em>Nature Climate Change</em> 10 (2): 155–61.</p>