Characterizing storm-induced coastal change hazards along the United States West Coast.

Traditional methods to assess the probability of storm-induced erosion and flooding from extreme water levels have limited use along the U.S. West Coast where swell dominates erosion and storm surge is limited. This effort presents methodology to assess the probability of erosion and flooding for the U.S. West Coast from extreme total water levels (TWLs), but the approach is applicable to coastal settings worldwide. TWLs were derived from 61 years of wave and water level data at shore-perpendicular transects every 100-m along open coast shorelines. At each location, wave data from the Global Ocean Waves model were downscaled to the nearshore and used to empirically calculate wave run-up. Tides were simulated using the Oregon State University's tidal data inversion model and non-tidal residuals were calculated from sea-surface temperature and pressure anomalies. Wave run-up was combined with still water levels to generate hourly TWL estimates and extreme TWLs for multiple return periods. Extremes were compared to onshore morphology to determine erosion hazards and define the probability of collision, overwash, and inundation.

Influence of postoperative complications on long-term survival in liver transplant patients.

BACKGROUND: Liver transplant (LT) is a complex procedure with frequent postoperative complications. In other surgical procedures such as gastrectomy, esophagectomy or resection of liver metastases, these complications are associated with poorer long-term survival. It is possible this happens in LT but there are not enough data to establish this relationship. AIM: To analyze the possible influence of postoperative complications on long-term survival and the ability of the comprehensive complication index (CCI) to predict this. METHODS: Retrospective study in a tertiary-level university hospital. The 164 participants were all patients who received a LT from January 2012 to July 2019. The follow-up was done in the hospital until the end of the study or death. Comorbidity and risk after transplantation were calculated using the Charlson and balance of risk (BAR) scores, respectively. Postoperative complications were graded according to the Clavien-Dindo classification and the CCI. To assess the CCI cut-off value with greater prognostic accuracy a receiver operating characteristic (ROC) curve was built, with calculation of the area under the curve (AUC). Overall survival was estimated according to the Kaplan-Meier test and log-rank test. Groups were compared by the Mann-Whitney test. For the multivariable analysis the Cox regression was used. RESULTS: The mean follow-up time of the cohort was 37.76 (SD = 24.5) mo. A ROC curve of CCI with 5-year survival was built. The AUC was 0.826 (0.730-0.922), P < 0.001. The cut-off was calculated by means of the Youden index with a result of 35.95. The sensitivity was 84.6% and the specificity 61.3%. Survival curves for comparison of patients with CCI score < 36 vs ≥ 36 were calculated. The estimated 5-year survival was 57.65 and 43.95 months, respectively (log-rank < 0.001). This suggests that patients with more severe complications exhibit worse long-term survival. Other cut-off values were analysed. Comparison between patients with CCI < 33.5 vs > 33.5 (33.5 = median CCI value) showed estimated 5-year survival was 57.4 and 45.71 months, respectively (log-rank < 0.0001). Dividing patients according to the mode CCI value (20.9) showed an estimated 5-year survival of 60 mo for a CCI below 20.9 vs 57 mo for a CCI above 20.9 (log-rank = 0.147). The univariate analysis did not show any association between individual complications and long-term survival. A multivariate analysis was carried out to analyse the possible influence of CCI, Charlson comorbidity index, BAR and hepatocellular carcinoma on survival. Only the CCI score showed significant influence on long-term survival. CONCLUSION: A complicated postoperative period - well-defined by means of the CCI score - can influence not only short-term survival, but also long-term survival.

Deep oil spill hazard assessment based on spatio-temporal met-ocean patterns.

Oil spill risk assessments are important tools for the offshore oil and gas industries to minimize the consequences of deep spills. The stochastic modeling required in this kind of studies, is generally centered on surface transport and based on a Monte Carlo selection of hundreds or thousands of met-ocean scenarios from reanalysis databases, to create an ensemble of spill simulations. We propose a new integrated stochastic modeling methodology including both surface and subsurface transport, based on the specific selection of the most relevant environmental conditions through data-mining techniques. The methodology was applied to evaluate oil contamination probability as a consequence of a simulated deep release in the North Sea. Our results show the effectiveness of the proposed methodology to select representative evolutions of met-ocean conditions and to obtain pollution probabilities from an integrated subsurface and surface oil spill stochastic modeling, while assuring a manageable computational effort.

Validation of the Balance of Risk as a Predictor of Liver Transplant Survival in a Spanish Population.

BACKGROUND: The Balance of Risk (BAR) score is a simple test that combines donor and recipient variables to predict liver transplant success. It has been validated in different publications, with cut-off points of between 15 and 18 points proposed depending on the region. The aim of this study is to test the validity of the BAR score and to find the optimal cut-off point for our population. MATERIALS AND METHODS: A retrospective cohort of 164 liver transplant patients was selected between January 2012 and July 2019. All were older than 18 years and were treated in a Spanish tertiary-level hospital. RESULTS: The receiver operating characteristic curve between BAR and 5-year survival yields a result of 0.622 (P = .046), placing the cut-off point at ≥7 (sensitivity 61.5%, specificity 61.6%). Patients with a BAR score <7 and a BAR score ≥7 have an estimated 5-year survival of 53.91 vs 47.51 months, respectively (log rank = .032). The only 2 variables associated with increased survival were a BAR score of <7 (hazard ratio = 2.566; P < .001) and a body mass index <30 (hazard ratio = 6.667; P < .001). CONCLUSIONS: A low BAR score correlates well with liver transplant survival at 5 years. The BAR is a simple tool that should be used for donor-recipient matching. Due to the characteristics, resources, and population in our environment, a BAR score of 7 would be the optimum cut-off point for a liver transplant.

Mid-long term oil spill forecast based on logistic regression modelling of met-ocean forcings.

Past major oil spill disasters, such as the Prestige or the Deepwater Horizon accidents, have shown that spilled oil may drift across the ocean for months before being controlled or reaching the coast. However, existing oil spill modelling systems can only provide short-term trajectory simulations, being limited by the typical met-ocean forecast time coverage. In this paper, we propose a methodology for mid-long term (1-6 months) probabilistic predictions of oil spill trajectories, based on a combination of data mining techniques, statistical pattern modelling and probabilistic Lagrangian simulations. Its main features are logistic regression modelling of wind and current patterns and a probabilistic trajectory map simulation. The proposed technique is applied to simulate the trajectory of drifting buoys deployed during the Prestige accident in the Bay of Biscay. The benefits of the proposed methodology with respect to existing oil spill statistical simulation techniques are analysed.

A methodology to assess the probability of marine litter accumulation in estuaries.

In this study, a general methodology that is based on numerical models and statistical analysis is developed to assist in the definition of marine litter cleanup and mitigation strategies at an estuarine scale. The methodology includes four main steps: k-means clustering to identify representative metocean scenarios; dynamic downscaling to obtain high-resolution drivers with which to force a transport model; numerical transport modelling to generate a database of potential litter trajectories; and a statistical analysis of this database to obtain probabilities of litter accumulation. The efficacy of this methodology is demonstrated by its application to an estuary along the northern coast of Spain by comparing the numerical results with field data. The necessary criteria to ensure its applicability to any other estuary were provided. As the main conclusion, the developed methodology successfully assesses the litter distribution in estuaries with minimum computational effort.

Operational oil spill trajectory modelling using HF radar currents: A northwest European continental shelf case study.

This paper presents a novel operational oil spill modelling system based on HF radar currents, implemented in a northwest European shelf sea. The system integrates Open Modal Analysis (OMA), Short Term Prediction algorithms (STPS) and an oil spill model to simulate oil spill trajectories. A set of 18 buoys was used to assess the accuracy of the system for trajectory forecast and to evaluate the benefits of HF radar data compared to the use of currents from a hydrodynamic model (HDM). The results showed that simulated trajectories using OMA currents were more accurate than those obtained using a HDM. After 48h the mean error was reduced by 40%. The forecast skill of the STPS method was valid up to 6h ahead. The analysis performed shows the benefits of HF radar data for operational oil spill modelling, which could be easily implemented in other regions with HF radar coverage.

A high-resolution operational forecast system for oil spill response in Belfast Lough.

This paper presents a high-resolution operational forecast system for providing support to oil spill response in Belfast Lough. The system comprises an operational oceanographic module coupled to an oil spill forecast module that is integrated in a user-friendly web application. The oceanographic module is based on Delft3D model which uses daily boundary conditions and meteorological forcing obtained from COPERNICUS and from the UK Meteorological Office. Downscaled currents and meteorological forecasts are used to provide short-term oil spill fate and trajectory predictions at local scales. Both components of the system are calibrated and validated with observational data, including ADCP data, sea level, temperature and salinity measurements and drifting buoys released in the study area. The transport model is calibrated using a novel methodology to obtain the model coefficients that optimize the numerical simulations. The results obtained show the good performance of the system and its capability for oil spill forecast.

Analysis of the reliability of a statistical oil spill response model.

A statistical oil spill response model is developed and validated by means of actual oil slick observations reported during the Prestige accident and trajectories of drifter buoys. The model is based on the analysis of a database of hypothetical oil spill scenarios simulated by means of a Lagrangian transport model. To carry out the simulations, a re-analysis database consisting of 44-year hindcast dataset of wind and waves and climatologic daily mean surface currents is used. The number of scenarios required to obtain statistically reliable results is investigated, finding that 200 scenarios provide an optimal balance between the accuracy of the results and the computational effort. The reliability of the model was analyzed by comparing the actual data with the numerical results. The agreement found between actual and numerical data shows that the developed statistical oil spill model is a valuable tool to support spill response planning.

Application of HF radar currents to oil spill modelling.

In this work, the benefits of high-frequency (HF) radar currents for oil spill modeling and trajectory analysis of floating objects are analyzed. The HF radar performance is evaluated by means of comparison between a drifter buoy trajectory and the one simulated using a Lagrangian trajectory model. A methodology to optimize the transport model performance and to calculate the search area of the predicted positions is proposed. This method is applied to data collected during the Galicia HF Radar Experience. This experiment was carried out to explore the capabilities of this technology for operational monitoring along the Spanish coast. Two long-range HF radar stations were installed and operated between November 2005 and February 2006 on the Galician coast. In addition, a drifter buoy was released inside the coverage area of the radar. The HF radar currents, as well as numerical wind data were used to simulate the buoy trajectory using the TESEO oil spill transport model. In order to evaluate the contribution of HF radar currents to trajectory analysis, two simulation alternatives were carried out. In the first one, wind data were used to simulate the motion of the buoy. In the second alternative, surface currents from the HF radar were also taken into account. For each alternative, the model was calibrated by means of the global optimization algorithm SCEM-UA (Shuffled Complex Evolution Metropolis) in order to obtain the probability density function of the model parameters. The buoy trajectory was computed for 24h intervals using a Monte Carlo approach based on the results provided in the calibration process. A bivariate kernel estimator was applied to determine the 95% confidence areas. The analysis performed showed that simulated trajectories integrating HF radar currents are more accurate than those obtained considering only wind numerical data. After a 24h period, the error in the final simulated position improves using HF radar currents. Averaging the information from all the simulated daily periods, the mean search and rescue area calculated using HF radar currents, is reduced by approximately a 62% in comparison with the search area calculated without these data. These results show the positive contribution of HF radar currents for trajectory analysis, and demonstrate that these data combined with atmospheric forecast models, are of value for trajectory analysis of oil spills or floating objects.