Detection and attribution of trends in magnitude, frequency and timing of floods in Spain

Mediero, Luis; Santillán, David; Garrote, Luís; Granados, Alfredo

doi:10.1016/j.jhydrol.2014.06.040

Cited by 106 publications

(86 citation statements)

References 47 publications

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“…In central Spain, Mediero et al (2014) found generally decreasing trends of annual maximum floods during , with the exception of a few gauging stations in the northwestern part of Spain which showed significantly increasing trends for that period. Similarly, decreasing trends in annual maximum floods were found in the Douro Basin during 1961(Morán-Tejeda et al, 2012.…”

Section: (I) Western Europe and Northern Europementioning

confidence: 83%

See 1 more Smart Citation

Understanding flood regime changes in Europe: a state-of-the-art assessment

Hall

Arheimer

Borga

et al. 2014

Hydrol. Earth Syst. Sci.

486

335

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Abstract. There is growing concern that flooding is becoming more frequent and severe in Europe. A better understanding of flood regime changes and their drivers is therefore needed. The paper reviews the current knowledge on flood regime changes in European rivers that has traditionally been obtained through two alternative research approaches. The first approach is the data-based detection of changes in observed flood events. Current methods are reviewed together with their challenges and opportunities. For example, observation biases, the merging of different data sources and accounting for nonlinear drivers and responses. The second approach consists of modelled scenarios of future floods. Challenges and opportunities associated with flood change scenarios are discussed such as fully accounting for uncertainties in the modelling cascade and feedbacks. To make progress in flood change research, we suggest that a synthesis of these two approaches is needed. This can be achieved by focusing on long duration records and flood-rich and flood-poor periods rather than on short duration flood trends only, by formally attributing causes of observed flood changes, by validating scenarios against observed flood regime dynamics, and by developing low-dimensional models of flood changes and feedbacks. The paper finishes with a call for a joint European flood change research network.

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Section: (I) Western Europe and Northern Europementioning

confidence: 83%

“…In Spanish Mediterranean catchments, generally decreasing trends in annual maximum floods during 1959-2009 were found (Mediero et al, 2014). In Catalonia, flash floods increased during the period 1982-2007 (Llasat et al, 2010), but decreased when the study was updated until 2010.…”

Section: (Iii) Mediterraneanmentioning

confidence: 88%

Understanding flood regime changes in Europe: a state-of-the-art assessment

Hall

Arheimer

Borga

et al. 2014

Hydrol. Earth Syst. Sci.

486

335

View full text Add to dashboard Cite

show abstract

“…The data-based attribution compares flood time series or their statistics with those of the assumed driver, for example, by evaluating the correlation between the time series of the potential cause and effect variables. It is common and widely used in the literature (e.g., [1,[6][7][8][9][10][11]). The simulation-based approach has been used in several studies with conceptual rainfall-runoff models [12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Climate or Land Use?—Attribution of Changes in River Flooding in the Sahel Zone

Aich

Liersch

Vetter

et al. 2015

Water

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This study intends to contribute to the ongoing discussion on whether land use and land cover changes (LULC) or climate trends have the major influence on the observed increase of flood magnitudes in the Sahel. A simulation-based approach is used for attributing the observed trends to the postulated drivers. For this purpose, the ecohydrological model SWIM (Soil and Water Integrated Model) with a new, dynamic LULC module was set up for the Sahelian part of the Niger River until Niamey, including the main tributaries Sirba and Goroul. The model was driven with observed, reanalyzed climate and LULC data for the years 1950-2009. In order to quantify the shares of influence, one simulation was carried out with constant land cover as of 1950, and one including LULC. As quantitative measure, the gradients of the simulated trends were compared to the observed trend. The modeling studies showed that for the Sirba River only the simulation which included LULC was able to reproduce the observed trend. The simulation without LULC showed a positive trend for flood magnitudes, but underestimated the trend significantly. For the Goroul River and the local flood of the Niger River at Niamey, the simulations were only partly able to reproduce the observed trend. In conclusion, the new LULC module OPEN ACCESSWater 2015, 7 2797 enabled some first quantitative insights into the relative influence of LULC and climatic changes. For the Sirba catchment, the results imply that LULC and climatic changes contribute in roughly equal shares to the observed increase in flooding. For the other parts of the subcatchment, the results are less clear but show, that climatic changes and LULC are drivers for the flood increase; however their shares cannot be quantified. Based on these modeling results, we argue for a two-pillar adaptation strategy to reduce current and future flood risk: Flood mitigation for reducing LULC-induced flood increase, and flood adaptation for a general reduction of flood vulnerability.

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“…Accordingly, there is a number of articles introducing methodology for change-points [Jarušková and Rencová, 2008;Kim and Lee, 2009;Dierckx and Teugels, 2010;Dupuis et al, 2015;Bücher et al, 2015;Kojadinovic and Naveau, 2015] and regression/trend analysis [Chavez-Demoulin and Davison, 2005;Wang and Tsai, 2009;Gardes and Girard, 2010;Dierckx, 2011;Wang et al, 2012;Wang and Li, 2013;Einmahl et al, 2016;de Haan et al, 2015] of extremes, just to name a few recent contributions. For a case study and an overview of many flood trend analyses we refer to Mediero et al [2014]. Our work is motivated by hydrological applications, where we aim at detecting smooth monotonic relationships between covariates X and the upper tail behavior of river discharges or precipitations Y , in particular, temporal trends in the tail behavior.…”

Section: Introductionmentioning

confidence: 99%

“…Our main interest is in testing the hypothesis H 0,tail : γpxq " γ 0 for some unknown γ 0 ą 0 of a constant heavy-tail behavior over all possible regressor values x P X . For that purpose, we also study a modification of Kendall's tau test statistic, where we apply the popular Mann-Kendall test (see Kendall [1948]; Yue et al [2002]; Chebana et al [2013]; Mediero et al [2014] and the references therein) to a properly selected upper fraction of the sample. We compare the performance of four different procedures that are constructed to detect deviations from H 0,tail and that are supposed to hold their nominal level in an asymptotic sense with sample size tending to infinity.…”

Section: Introductionmentioning

confidence: 99%

Conditional heavy-tail behavior with applications to precipitation and river flow extremes

Kinsvater

Fried

2016

Stoch Environ Res Risk Assess

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This article deals with the right-tail behavior of a response distribution F Y conditional on a regressor vector X " x restricted to the heavy-tailed case of Pareto-type conditional distributions F Y py| xq " P pY ď y| X " xq, with heaviness of the right tail characterized by the conditional extreme value index γpxq ą 0. We particularly focus on testing the hypothesis H 0,tail : γpxq " γ 0 of constant tail behavior for some γ 0 ą 0 and all possible x. When considering x as a time index, the term trend analysis is commonly used. In the recent past several such trend analyses in extreme value data have been published, mostly focusing on time-varying modeling of location and scale parameters of the response distribution. In many such environmental studies a simple test against trend based on Kendall's tau statistic is applied. This test is powerful when the center of the conditional distribution F Y py|xq changes monotonically in x, for instance, in a simple location model µpxq " µ 0`x¨µ1 , x " p1, xq 1 , but the test is rather insensitive against monotonic tail behavior, say, γpxq " η 0`x¨η1 . This has to be considered, since for many environmental applications the main interest is on the tail rather than the center of a distribution. Our work is motivated by this problem and it is our goal to demonstrate the opportunities and the limits of detecting and estimating non-constant conditional heavy-tail behavior with regard to applications from hydrology. We present and compare four different procedures by simulations and illustrate our findings on real data from hydrology: Weekly maxima of hourly precipitation from France and monthly maximal river flows from Germany.

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Detection and attribution of trends in magnitude, frequency and timing of floods in Spain

Cited by 106 publications

References 47 publications

Understanding flood regime changes in Europe: a state-of-the-art assessment

Understanding flood regime changes in Europe: a state-of-the-art assessment

Climate or Land Use?—Attribution of Changes in River Flooding in the Sahel Zone

Conditional heavy-tail behavior with applications to precipitation and river flow extremes

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