Climate change has led to concerns about increasing river floods resulting from the greater water-holding capacity of a warmer atmosphere 1 . These concerns are reinforced by evidence of increasing economic losses associated with flooding in many parts of the world, including Europe 2 . Any changes in river floods would have lasting implications for the design of flood protection measures and flood risk zoning. However, existing studies have been unable to identify a consistent continental-scale climatic-change signal in flood discharge observations in Europe 3 , because of the limited spatial coverage and number of hydrometric stations. Here we demonstrate clear regional patterns of both increases and decreases in observed river flood discharges in the past five decades in Europe, which are manifestations of a changing climate. Our results-arising from the most complete database of European flooding so farsuggest that: increasing autumn and winter rainfall has resulted in increasing floods in northwestern Europe; decreasing precipitation and increasing evaporation have led to decreasing floods in medium and large catchments in southern Europe; and decreasing snow cover and snowmelt, resulting from warmer temperatures, have led to decreasing floods in eastern Europe. Regional flood discharge trends in Europe range from an increase of about 11 per cent per decade to a decrease of 23 per cent. Notwithstanding the spatial and temporal heterogeneity of the observational record, the flood changes identified here are broadly consistent with climate model projections for the next century 4,5 , suggesting that climatedriven changes are already happening and supporting calls for the consideration of climate change in flood risk management.River floods are among the most costly natural hazards. Global annual average losses are estimated at US$104 billion 6 and are expected to increase with economic growth, urbanization and climatic change 2,7 . Physical arguments of increased heavy precipitation resulting from the enhanced water-holding capacity of a warmer atmosphere and

[1] A distance-based regionalization model is developed for the estimation of dimensionless flow duration curves (FDC) in sites with no or limited available data. The curves are dimensionless because they are preliminarily normalized by an index value (e.g., the mean annual runoff). The model aims at representing the FDC as a nonparametric object rather than providing a parametric representation and trying to relate the parameter values to basin descriptors. The regional approach considers the (dis)similarity between all possible pairs of curves and uses distance measures that can be related to basin descriptors, taken among geographic, geomorphologic, and climatic parameters. The (dis)similarity between curves is computed using a predefined metric based on a linear norm and produces a distance matrix. This matrix is then related, by means of linear regression models, to analogous matrices composed of the difference between all possible values of each descriptor within the set of basins. After identification of significant descriptors, a cluster analysis is applied so that the basins can be grouped together. Each region is supposed to be characterized by a single dimensionless flow duration curve. The procedure is applied to 95 basins located in northwestern Italy and Switzerland. The performance in the regional estimation is assessed by means of a cross-validation procedure through comparison with ''standard'' parametric regional approaches based on two-and three-parameter models. In most of the cases, the distance-based model produces better estimates of the flow duration curves using only few catchment descriptors.Citation: Ganora, D., P. Claps, F. Laio, and A. Viglione (2009), An approach to estimate nonparametric flow duration curves in ungauged basins, Water Resour. Res., 45, W10418,

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Hydraulic infrastructures are commonly designed with reference to target values of flood peak, estimated using probabilistic techniques, such as flood frequency analysis. The application of these techniques underlies levels of uncertainty, which are sometimes quantified but normally not accounted for explicitly in the decision regarding design discharges. The present approach aims at defining a procedure which enables the definition of Uncertainty Compliant Design (UNCODE) values of flood peaks. To pursue this goal, we first demonstrate the equivalence of the Standard design based on the return period and the costbenefit procedure, when linear cost and damage functions are used. We then use this result to assign an expected cost to estimation errors, thus setting a framework to obtain a design flood estimator which minimizes the total expected cost. This procedure properly accounts for the uncertainty which is inherent in the frequency curve estimation. Applications of the UNCODE procedure to real cases leads to remarkable displacement of the design flood from the Standard values. UNCODE estimates are systematically larger than the Standard ones, with substantial differences (up to 55%) when large return periods or short data samples are considered.

The widespread perception of an increase in the severity of extreme rainstorms has not found yet clear confirmation in the scientific literature, often showing vastly different results. Especially for short‐duration extremes, spatial heterogeneities can affect the outcomes of large‐scale trend analyses, providing misleading results dependent on the adopted spatial domain. Based on the availability of a renewed and comprehensive database, the present work assesses the presence of regional trends in the magnitude and frequency of annual rainfall maxima for subdaily durations in Italy. Versions of the Mann‐Kendall test and a record‐breaking analysis, which considers the spatial correlation, have been adopted for the scope. Significant trends do not appear at the whole‐country scale, but distinct patterns of change emerge in smaller domains having homogeneous geographical characteristics. Results of the study underline the importance of a multiscale approach to regional trend analysis and the need of more advanced explanations of localized trends.