Abstract. The

There has been a surprisingly large number of major floods in the last years around the world, which suggests that floods may have increased and will continue to increase in the next decades. However, the realism of such changes is still hotly discussed in the literature. This overview article examines whether floods have changed in the past and explores the driving processes of such changes in the atmosphere, the catchments and the river system based on examples from Europe. Methods are reviewed for assessing whether floods may increase in the future. Accounting for feedbacks within the human-water system is important when assessing flood changes over lead times of decades or centuries. It is argued that an integrated flood risk management approach is needed for dealing with future flood risk with a focus on reducing the vulnerability of the societal system.

Changes in the river flood regime may be due to atmospheric processes (e.g., increasing precipitation), catchment processes (e.g., soil compaction associated with land use change), and river system processes (e.g., loss of retention volume in the floodplains). This paper proposes a new framework for attributing flood changes to these drivers based on a regional analysis. We exploit the scaling characteristics (i.e., fingerprints) with catchment area of the effects of the drivers on flood changes. The estimation of their relative contributions is framed in Bayesian terms. Analysis of a synthetic, controlled case suggests that the accuracy of the regional attribution increases with increasing number of sites and record lengths, decreases with increasing regional heterogeneity, increases with increasing difference of the scaling fingerprints, and decreases with an increase of their prior uncertainty. The applicability of the framework is illustrated for a case study set in Austria, where positive flood trends have been observed at many sites in the past decades. The individual scaling fingerprints related to the atmospheric, catchment, and river system processes are estimated from rainfall data and simple hydrological modeling. Although the distributions of the contributions are rather wide, the attribution identifies precipitation change as the main driver of flood change in the study region. Overall, it is suggested that the extension from local attribution to a regional framework, including multiple drivers and explicit estimation of uncertainty, could constitute a similar shift in flood change attribution as the extension from local to regional flood frequency analysis.

The June 2013 flood in the Upper Danube basin was one of the largest floods in the past two centuries. An atmospheric blocking situation produced precipitation exceeding 300 mm over four days at the northern rim of the Alps. The high precipitation along with high antecedent soil moisture gave rise to extreme flood discharges in a number of tributaries including the Tiroler Ache, Saalach, Salzach and Inn. Runoff coefficients ranged from 0.2 in the Bavarian lowlands to 0.6 in the Alpine areas in Austria. Snowfall at high altitudes (above about 1600 m a.s.l.) reduced the runoff volume produced. Precipitation was distributed over two blocks separated by a few hours which resulted in a single peak, long duration flood wave at the Inn and Danube. At the confluence of the Bavarian Danube and the Inn, the small time lag between the two flood waves exacerbated the downstream flood at the Danube. Because of the long duration and less inundation, there was less flood peak attenuation along the Austrian Danube reach than for the August 2002 flood. Maximum flood discharges of the Danube at Vienna were about 11 000 m³ s⁻¹, as compared to 10 300, 9600 and 10 500 m³ s⁻¹ in 2002, 1954 and 1899, respectively. This paper reviews the meteorological and hydrological characteristics of the event as compared to the 2002, 1954 and 1899 floods, and discusses the implications for hydrological research and flood risk management

[1] Flood forecasts are generally associated with errors, which can be attributed to uncertainties in the meteorological forecasts and the hydrologic simulations, and ensemble spreads are usually considered capable of representing them. To quantify these two components of the total forecast errors and to compare these to ensemble spreads, an extended data set is used. Four years of operational flood forecasts at hourly time step with lead times up to 48 h are evaluated for 43 catchments in Austria and Germany. Catchment sizes range from 70 to 25,600 km 2 , elevations from 200 to 3800 m, and mean annual precipitation from 700 to 2000 mm. A combination of ECMWF and ALADIN ensemble forecasts are used as input in a semidistributed conceptual water balance model on an hourly time step. The results indicate that, for short lead times, the ratio of hydrological simulation error to precipitation forecast error is 1.2 to 2.7 with increasing catchment size from 100 to 10,000 km 2 . For long lead times the ratio of hydrological simulation error to precipitation forecast error decreases from 1.1 to 0.9 with increasing catchment size. Clear scaling relationships of the forecast error components with catchment area are found. A similar scaling is also found for ensemble spreads, which are shown to represent quantitatively the total forecast error when forecasting floods.