Assessing the hydrodynamic boundary conditions for risk analyses in coastal areas: a multivariate statistical approach based on Copula functions

This paper presents an advanced approach to statistically analyse storm surge events. In former studies the highest water level during a storm surge event usually was the only parameter that was used for the statistical assessment. This is not always sufficient, especially when statistically analysing storm surge scenarios for event-based risk analyses. Here, Archimedean Copula functions are applied and allow for the consideration of further important parameters in addition to the highest storm surge water levels. First, a bivariate model is presented and used to estimate exceedance probabilities of storm surges (for two tide gauges in the German Bight) by jointly analysing the important storm surge parameters "highest turning point" and "intensity". Second, another dimension is added and a trivariate fully nested Archimedean Copula model is applied to additionally incorporate the significant wave height as an important wave parameter. With the presented methodology, reliable and realistic exceedance probabilities are derived and can be considered (among others) for integrated flood risk analyses contributing to improve the overall results. It is highlighted that the concept of Copulas represents a promising alternative for facing multivariate problems in coastal engineering.<br/

Changes in extreme sea-levels in the Baltic Sea

In a climate change context, changes in extreme sea-levels rather than changes in the mean are of particular interest from the coastal protection point of view. In this work, extreme sea-levels in the Baltic Sea are investigated based on daily tide gauge records for the period 1916–2005 using the annual block maxima approach. Extreme events are analysed based on the generalised extreme value distribution considering both stationary and time-varying models. The likelihood ratio test is applied to select between stationary and non-stationary models for the maxima and return values are estimated from the final model. As an independent and complementary approach, quantile regression is applied for comparison with the results from the extreme value approach. The rates of change in the uppermost quantiles are in general consistent and most pronounced for the northernmost stations

Effect of FeO on the formation of spinel phases and chromium distribution in the CaO-SiO2-MgO-Al2O3-Cr2O3 system

Synthetic slag samples of the CaO-SiO2-MgO-Al2O3-Cr2O3 system were obtained to clarify the effect of FeO on the formation of spinel phases and Cr distribution. X-ray diffraction (XRD) and scanning electron microscopy (SEM) equipped with energy-dispersive spectroscopy (EDS), as well as the thermodynamic software FactSage 6.2, were used for sample characterization. The results show that the addition of FeO can decrease the viscosity of molten slag and the precipitation temperatures of melilite and merwinite. The solidus temperature significantly decreases from 1400 to 1250 degrees C with the increase of FeO content from 0wt% to 6wt%. The addition of FeO could enhance the content of Cr in spinel phases and reduce the content of Cr in soluble minerals, such as merwinite, melilite, and dicalcium silicate. Hence, the addition of FeO is conducive to decreasing Cr leaching.Validerad; 2013; 20130411 (andbra

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

Effect of remote ischaemic conditioning on clinical outcomes in patients with acute myocardial infarction (CONDI-2/ERIC-PPCI): a single-blind randomised controlled trial.

BACKGROUND: Remote ischaemic conditioning with transient ischaemia and reperfusion applied to the arm has been shown to reduce myocardial infarct size in patients with ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). We investigated whether remote ischaemic conditioning could reduce the incidence of cardiac death and hospitalisation for heart failure at 12 months. METHODS: We did an international investigator-initiated, prospective, single-blind, randomised controlled trial (CONDI-2/ERIC-PPCI) at 33 centres across the UK, Denmark, Spain, and Serbia. Patients (age >18 years) with suspected STEMI and who were eligible for PPCI were randomly allocated (1:1, stratified by centre with a permuted block method) to receive standard treatment (including a sham simulated remote ischaemic conditioning intervention at UK sites only) or remote ischaemic conditioning treatment (intermittent ischaemia and reperfusion applied to the arm through four cycles of 5-min inflation and 5-min deflation of an automated cuff device) before PPCI. Investigators responsible for data collection and outcome assessment were masked to treatment allocation. The primary combined endpoint was cardiac death or hospitalisation for heart failure at 12 months in the intention-to-treat population. This trial is registered with ClinicalTrials.gov (NCT02342522) and is completed. FINDINGS: Between Nov 6, 2013, and March 31, 2018, 5401 patients were randomly allocated to either the control group (n=2701) or the remote ischaemic conditioning group (n=2700). After exclusion of patients upon hospital arrival or loss to follow-up, 2569 patients in the control group and 2546 in the intervention group were included in the intention-to-treat analysis. At 12 months post-PPCI, the Kaplan-Meier-estimated frequencies of cardiac death or hospitalisation for heart failure (the primary endpoint) were 220 (8·6%) patients in the control group and 239 (9·4%) in the remote ischaemic conditioning group (hazard ratio 1·10 [95% CI 0·91-1·32], p=0·32 for intervention versus control). No important unexpected adverse events or side effects of remote ischaemic conditioning were observed. INTERPRETATION: Remote ischaemic conditioning does not improve clinical outcomes (cardiac death or hospitalisation for heart failure) at 12 months in patients with STEMI undergoing PPCI. FUNDING: British Heart Foundation, University College London Hospitals/University College London Biomedical Research Centre, Danish Innovation Foundation, Novo Nordisk Foundation, TrygFonden

An analysis of changes in flood quantiles at the gauge Neu Darchau (Elbe River) from 1875 to 2013

Within this investigation, we focus on a detailed analysis of the discharge data of the gauge Neu Darchau (Elbe River). The Elbe River inflows onto the North Sea. The gauge Neu Darchau is the most downstream discharge gauge of the Elbe River before it becomes an estuary. We follow the questions, whether the discharge characteristics of the Elbe River have changed over the last decades and how much common flood quantiles (i.e. 100-year flood) are affected by the latest extreme events in 2002, 2006, 2011, and 2013. Hence, we conduct (i) trend and seasonality analysis and (ii) an assessment of time-dependencies of flood quantiles by using quasi non-stationary extreme value statistics with both block maxima and peak-over-threshold approaches. The (iii) significance of the changes found in flood quantiles are assessed by using a stochastic approach based on autoregressive models and Monte Carlo simulations. The results of the trend analyses do show no clear evidences for any significant trends in daily mean discharges and increasing flood frequencies. With respect to the extreme events in 2002, 2006, 2011, and 2013 our results reveal, that those events do not lead to extraordinary changes in the 100-year floods. Nevertheless, in the majority an increase in the 100-year floods over the recent decades can be stated. Although these changes are not significant, for many time series of the 100-year flood quantiles there is a clear tendency towards the upper confidence band

Statistical assessment of storm surge scenarios within integrated risk analyses

This paper summarizes the results from calculating exceedance probabilities of different storm surge scenarios developed within the XtremRisK project, which were then used as boundary conditions for integrated risk analyses for the city of Hamburg in the Elbe Estuary and Sylt Island off the coastline of Schleswig-Holstein in northern Germany. A stochastic storm surge model is developed to simulate a large number of synthetic and physically consistent storm surge scenarios, before the resulting samples are used to calculate bivariate joint exceedance probabilities of the storm surge heights (total water levels with tides included) and intensities. The Copula theory is exploited and functions from the Archimedean family are used to build the statistical models. The latter are extended to the three-dimensional case to also take into account wave conditions where appropriate. The uncertainties associated with the results from the multivariate extreme value analyses are briefly discussed and (where possible) quantified and recommendations of how to exploit the presented methodologies in future applications are given.<br/