Climate influences on flood probabilities across Europe

Steirou, Eva; Gerlitz, Lars; Apel, Heiko; Sun, Xun; Merz, Bruno

doi:10.5194/hess-23-1305-2019

Cited by 42 publications

(38 citation statements)

References 60 publications

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“…Figures 4and 5 (and the associated figures in the appendix) indicate that, in northwestern Europe, the frequency of stations with flood-rich periods has been increasing since around 1980. The alignment between flood occurrence and NAO is consistent with other studies Steirou et al (2019). report a strong influence of the NAO on floods in northwestern Europe, especially in winter, andZanardo et al (2019) show a strong correlation between the NAO and flood losses.…”

supporting

confidence: 92%

Detecting Flood‐Rich and Flood‐Poor Periods in Annual Peak Discharges Across Europe

Lun

Fischer

Viglione

et al. 2020

Water Resources Research

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This paper proposes a method from Scan statistics for identifying flood‐rich and flood‐poor periods (i.e., anomalies) in flood discharge records. Exceedances of quantiles with 2‐, 5‐, and 10‐year return periods are used to identify periods with unusually many (or few) threshold exceedances with respect to the reference condition of independent and identically distributed random variables. For the case of flood‐rich periods, multiple window lengths are used in the identification process. The method is applied to 2,201 annual flood peak series in Europe between 1960 and 2010. Results indicate evidence for the existence of flood‐rich and flood‐poor periods, as about 2 to 3 times more anomalies are detected than what would be expected by chance. The frequency of the anomalies tends to decrease with an increasing threshold return period which is consistent with previous studies, but this may be partly related to the method and the record length of about 50 years. In the northwest of Europe, the frequency of stations with flood‐rich periods tends to increase over time and the frequency of stations with flood‐poor periods tends to decrease. In the east and south of Europe, the opposite is the case. There appears to exist a turning point around 1970 when the frequencies of anomalies start to change most clearly. This turning point occurs at the same time as a turning point of the North Atlantic Oscillation index. The method is also suitable for peak‐over‐threshold series and can be generalized to higher dimensions, such as space and space‐time.

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supporting

confidence: 92%

Detecting Flood‐Rich and Flood‐Poor Periods in Annual Peak Discharges Across Europe

Lun

Fischer

Viglione

et al. 2020

Water Resources Research

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“…Spatial cross-correlation between flood time series at different sites is not accounted for in this model and may affect the estimation of sampling uncertainty (see e.g. Stedinger, 1983;Castellarin et al, 2008;Sun et al, 2014). Because of this, the sampling uncertainties estimated in this paper should be considered as a lower boundary.…”

Section: Discussionmentioning

confidence: 99%

“…Cunderlik and Burn, 2003;Renard et al, 2006a;Leclerc and Ouarda, 2007;Hanel et al, 2009;Roth et al, 2012) or on climatic and anthropogenic covariates (e.g. Lima and Lall, 2010;Tramblay et al, 2013;Renard and Lall, 2014;Sun et al, 2014;Prosdocimi et al, 2015;Viglione et al, 2016). Other approaches analyse coherent regional change by testing for the presence of trends in regional variables, as the number of annual floods in the region (e.g.…”

Section: Introductionmentioning

confidence: 99%

Flood trends in Europe: are changes in small and big floods different?

Bertola

Viglione

Lun

et al. 2020

Hydrol. Earth Syst. Sci.

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Abstract. Recent studies have revealed evidence of trends in the median or mean flood discharge in Europe over the last 5 decades, with clear and coherent regional patterns. The aim of this study is to assess whether trends in flood discharges also occurred for larger return periods, accounting for the effect of catchment scale. We analyse 2370 flood discharge records, selected from a newly available pan-European flood database, with record length of at least 40 years over the period 1960–2010 and with contributing catchment area ranging from 5 to 100 000 km2. To estimate regional flood trends, we use a non-stationary regional flood frequency approach consisting of a regional Gumbel distribution, whose median and growth factor can vary in time with different strengths for different catchment sizes. A Bayesian Markov chain Monte Carlo (MCMC) approach is used for parameter estimation. We quantify regional trends (and the related sample uncertainties), for floods of selected return periods and for selected catchment areas, across Europe and for three regions where coherent flood trends have been identified in previous studies. Results show that in northwestern Europe the trends in flood magnitude are generally positive. In small catchments (up to 100 km2), the 100-year flood increases more than the median flood, while the opposite is observed in medium and large catchments, where even some negative trends appear, especially in northwestern France. In southern Europe flood trends are generally negative. The 100-year flood decreases less than the median flood, and, in the small catchments, the median flood decreases less compared to the large catchments. In eastern Europe the regional trends are negative and do not depend on the return period, but catchment area plays a substantial role: the larger the catchment, the more negative the trend.

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“…These studies typically allowed the parameters of the probability distribution of floods to vary in time, using time-varying climatic covariates (e.g. Prosdocimi et al, 2014;Šraj et al, 2016;Steirou et al, 2019) and, more rarely, catchment and river covariates (e.g. López and Francés, 2013;Silva et al, 2017;Bertola et al, 2019).…”

mentioning

confidence: 99%

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

Bertola¹,

Viglione²,

Vorogushyn³

et al. 2020

Preprint

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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.

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Climate influences on flood probabilities across Europe

Cited by 42 publications

References 60 publications

Detecting Flood‐Rich and Flood‐Poor Periods in Annual Peak Discharges Across Europe

Detecting Flood‐Rich and Flood‐Poor Periods in Annual Peak Discharges Across Europe

Flood trends in Europe: are changes in small and big floods different?

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

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