Applying POT methods to the Revised Joint Probability Method for determining extreme sea levels

Mazas, Franck; Kergadallan, Xavier; Garat, Philippe; Hamm, Luc

doi:10.1016/j.coastaleng.2014.05.006

Cited by 32 publications

(34 citation statements)

References 16 publications

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“…Previous studies have tended to focus separately on either 'extreme' [4,10] sea levels or 'nuisance' [1] flooding. We have used a mixed-distribution model [36,37], which allows us to estimate the changing frequency of smaller, more frequent storm-tides which are used to design signals and triggers, while simultaneously modelling the changing frequency of more extreme storm-tides as adaptation-thresholds to be avoided. The mixed distributions for six NZ coastalgauge sites are shown in figure 2, and compared with Auckland (NZ) at six international sites in figure 3.…”

Section: Summary Of Detailed Methodsmentioning

confidence: 99%

Developing signals to trigger adaptation to sea-level rise

Stephens

Bell

Lawrence

2018

Environ. Res. Lett.

106

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Dynamic adaptive policy pathways (DAPP) is emerging as a 'fit-for-purpose' method for climatechange adaptation planning to address widening future uncertainty and long planning timeframes. A key component of DAPP is to monitor indicators of change such as flooding and storm events, which can trigger timely adaptive actions (change pathway/behavior) ahead of thresholds. Signals and triggers are needed to support DAPP-the signal provides early warning of the emergence of the trigger (decision-point), and the trigger initiates the process to change pathway before a harmful adaptation-threshold is reached. We demonstrate a new approach to designing signals and triggers using the case of increased flooding as sea level continues to rise. The flooding frequency is framed in terms of probable timing of several events reaching a specific height threshold within a set monitoring period. This framing is well suited to adaptive planning for different hazards, because it allows the period over which threshold exceedances are monitored to be specified, and thus allows action before adaptation-thresholds are reached, while accounting for the potential range of timing and providing a probability of premature warning, or of triggering adaptation too late. For our New Zealand sea level case study, we expect early signals to be observed in 10 year monitoring periods beginning 2021. Some urgency is therefore required to begin the assessment, planning and community engagement required to develop adaptive plans and associated signals and triggers for monitoring. Worldwide, greater urgency is required at tide-dominated sites than those adapted to large storm-surges. Triggers can be designed with confidence that a change in behavior pathway (e.g. relocating communities) will be triggered before an adaptation-threshold occurs. However, it is difficult to avoid the potential for premature adaptation. Therefore, political, social, economic, or cultural signals are also needed to complement the signals and triggers based on coastal-hazard considerations alone.

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Section: Summary Of Detailed Methodsmentioning

confidence: 99%

Developing signals to trigger adaptation to sea-level rise

Stephens

Bell

Lawrence

2018

Environ. Res. Lett.

106

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“…Such an indi-rect method assumes surges and tides are independent. This assumption being wrong in some places (Idier et al, 2012), methods have been developed to take into account this partial dependency (Mazas et al, 2014). However, the results are not yet fully satisfactory, with for instance a notable offset between direct and indirect methods within the interpolation domain (i.e.…”

Section: Introductionmentioning

confidence: 99%

How historical information can improve estimation and prediction of extreme coastal water levels: application to the Xynthia event at La Rochelle (France)

Bulteau

Idier

Lambert

et al. 2015

Nat. Hazards Earth Syst. Sci.

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Abstract. The knowledge of extreme coastal water levels is useful for coastal flooding studies or the design of coastal defences. While deriving such extremes with standard analyses using tide-gauge measurements, one often needs to deal with limited effective duration of observation which can result in large statistical uncertainties. This is even truer when one faces the issue of outliers, those particularly extreme values distant from the others which increase the uncertainty on the results. In this study, we investigate how historical information, even partial, of past events reported in archives can reduce statistical uncertainties and relativise such outlying observations. A Bayesian Markov chain Monte Carlo method is developed to tackle this issue. We apply this method to the site of La Rochelle (France), where the storm Xynthia in 2010 generated a water level considered so far as an outlier. Based on 30 years of tide-gauge measurements and 8 historical events, the analysis shows that (1) integrating historical information in the analysis greatly reduces statistical uncertainties on return levels (2) Xynthia's water level no longer appears as an outlier, (3) we could have reasonably predicted the annual exceedance probability of that level beforehand (predictive probability for 2010 based on data until the end of 2009 of the same order of magnitude as the standard estimative probability using data until the end of 2010). Such results illustrate the usefulness of historical information in extreme value analyses of coastal water levels, as well as the relevance of the proposed method to integrate heterogeneous data in such analyses.

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“…Coles, 2001;Thompson et al, 2009). The objective is to automatically create thresholds that reliably reflect those widely produced by the many practitioners who use the graphical approach (Solari and Losada, 2012b;Agarwal et al, 2013;Bernardara et al, 2014;Mazas et al, ).…”

Section: Discussionmentioning

confidence: 99%

“…However, despite the extent and rigour of this work, percentile selection (e.g. 95th or 99th) by parametric means or otherwise is ultimately a subjective procedure (Arns et al, 2013), and even mixture models do not produce a decisive verdict as evidenced by the variety of mixtures proposed (Scarrott and MacDonald, 2012;Solari and Losada, 2012a;Mazas et al, ). In parallel, Li et al (2014) recently proposed a fourth way to select thresholds based on the root mean square error (RMSE) between empirical and analytical cumulative distribution functions (cdf ).…”

Section: Introductionmentioning

confidence: 99%

Technical note: comparison of methods for threshold selection for extreme sea levels

Caballero-Megido

Hillier

Wyncoll

et al. 2017

J Flood Risk Management

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Extreme value analysis is an important tool for studying coastal flood risk, but requires the estimation of a threshold to define an ‘extreme’, which is traditionally undertaken visually. Such subjective judgement is not accurately reproducible, so recently a number of quantitative approaches have been proposed. This paper therefore reviews existing methods, illustrated with coastal tide‐gauge data and the Generalized Pareto Distribution, and proposes a new automated method that mimics the enduringly popular visual inspection method. In total, five different types of statistical threshold selection and their variants are evaluated by comparison to manually derived thresholds, demonstrating that the new method is a useful, complementary tool.

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Applying POT methods to the Revised Joint Probability Method for determining extreme sea levels

Cited by 32 publications

References 16 publications

Developing signals to trigger adaptation to sea-level rise

Developing signals to trigger adaptation to sea-level rise

How historical information can improve estimation and prediction of extreme coastal water levels: application to the Xynthia event at La Rochelle (France)

Technical note: comparison of methods for threshold selection for extreme sea levels

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