Do small and large floods have the same drivers of change? A regional attribution analysis in Europe

Abstract

Abstract. Recent studies have shown evidence of increasing and decreasing trends in mean annual floods and flood quantiles across Europe. Studies attributing observed changes in flood peaks to their drivers have mostly focused on mean annual floods. This paper proposes a new framework for attributing flood changes to potential drivers, as a function of return period (T), in a regional context. We assume flood peaks to follow a non-stationary regional Gumbel distribution, where the median flood and the 100-year growth factor are used as parameters. They are allowed to vary in time and between catchments as a function of the drivers quantified by covariates. The elasticities of floods with respect to the drivers and the contributions of the drivers to flood changes are estimated by Bayesian inference. The prior distributions of the elasticities of flood quantiles to the drivers are estimated by hydrological reasoning and from the literature. The attribution model is applied to European flood and covariate data and aims at attributing the observed flood trend patterns to specific drivers for different return periods. We analyse flood discharge records from 2370 hydrometric stations in Europe over the period 1960–2010. Extreme precipitation, antecedent soil moisture and snowmelt are the potential drivers of flood change considered in this study. Results show that, in northwestern Europe, extreme precipitation mainly contributes to changes in both the median (q2) and 100-year flood (q100), while the contributions of antecedent soil moisture are of secondary importance. In southern Europe, both antecedent soil moisture and extreme precipitation contribute to flood changes, and their relative importance depends on the return period. Antecedent soil moisture is the main contributor to changes in q2, while the contributions of the two drivers to changes in larger floods (T > 10 years) are comparable. In eastern Europe, snowmelt drives changes in both q2 and q100.

Understanding the impacts of predecessor rain events on flood hazard in a changing climate

“…However, we find that an apparent trend is missing between the number of lagged days of PREs and the catchment area for extreme flood events. The specific insight corroborates with an earlier study (Bertola et al, 2021), where authors have used a longer temporal window (up to 1 month) for antecedent precipitation to assess the influence of antecedent soil moisture as a potential driver for flood genesis. However, they could not detect any specific trend in terms of the long‐term evolution of the driver, even for large catchments.…”

“…The concurrence of PRE with antecedent conditions, for example, Antecedent Moisture Condition (AMC), amplifies the soil moisture level. Following earlier studies (Bertola et al, 2021), we apply the AMC‐based index as an accumulated lagged‐daily precipitation record instead of modelled soil moisture to rely strongly on station‐based observation.…”

Event and Catchment Controls of Heavy Tail Behavior of Floods

“…The width of the window is estimated according to Bertola et al. (2020) and depends on the concentration of occurrence dates around MD. We use the GEV shape parameter of all MP ( MP_shape ) in a catchment as a potential predictor.…”

HOchwasserRisikozonierung Austria 3.0 (HORA 3.0)

“…Für den Zeitraum 1976-2014 zeigen 34 % der gemessenen Abflussreihen nördlich des Alpenhauptkamms einen signifikanten steigenden Trend, während es im Süden 15 % sind. Die Gründe für diese Änderungen wurden umfangreich analysiert (Blöschl et al 2015a;Bertola et al 2021;Merz et al 2021) und es ist klar, dass der Klimawandel einen Beitrag leistet. Deshalb war es notwendig, die Hochwassergefahr auf Basis der aktualisierten Abflussdatenreihen neu zu bewerten.…”

“…Die HQ100 an den Pegeln sind wegen der in der Zwischenzeit aufgetretenen großen Hochwasser im Durchschnitt um 8,7 % höher als die entsprechenden Werte in HORA 1.0. Diese Erhöhung ist in Übereinstimmung mit den in Blöschl et al (2018) festgestellten Veränderungen der Hochwasserabflüsse, und ist teilweise auf eine veränderte klimatische Situation zurückzuführen (Blöschl et al 2019;Bertola et al 2021). Adaptierte Versionen des Geländemodells vom Dezember 2015 liegen vor, z.…”