Ocean state rising: Storm simulation and vulnerability mapping to predict hurricane impacts for Rhode Island's critical infrastructure.

Predicting the consequences of a major coastal storm is increasingly difficult as the result of global climate change and growing societal dependence on critical infrastructure (CI). Past storms are no longer a reliable predictor of future weather events, and the traditional approach to vulnerability assessment presents accumulated loss in largely quantitative terms that lack the specificity local emergency managers need to develop effective plans and mitigation strategies. The Rhode Island Coastal Hazards Modeling and Prediction (RI-CHAMP) system is a geographic information system (GIS)-based modeling tool that combines high-resolution storm simulations with geolocated vulnerability data to predict specific consequences based on local concerns about impacts to CI. This case study discusses implementing RI-CHAMP for the State of Rhode Island to predict impacts of wind and inundation on its CI during a hurricane, tropical storm, or nor'easter. This paper addresses the collection and field verification of vulnerability data, along with RI-CHAMP's process for integrating those data with storm models. The project deeply engaged end-users (emergency managers, facility managers, and other stakeholders) in developing RI-CHAMP's ArcGIS Online dashboard to ensure it provides specific, actionable data. The results of real and synthetic storm models are presented along with discussion of how the data in these simulations are being used by state and local emergency managers, facility owners, and others.

Counter-historical study of alternative dispersant use in the Deepwater Horizon oil spill response.

Recent completion of oil fate modeling and a mass budget of the Deepwater Horizon (DWH) oil spill allows for a counter-historical study using quantitative Comparative Risk Assessment (CRA) methodology. Novel application of subsea dispersant injection (SSDI) during the response reduced surfacing oil, volatile organic carbon emissions, and oil on shorelines. The effectiveness of that application, and potential alternatives had dispersant not been used or been used more aggressively, were evaluated by modifying and comparing the validated oil fate model under different SSDI strategies. A comparison of mass balance results, exposure metrics, and CRA scoring for Valued Ecological Components (VECs) shows the value of SSDI in achieving risk reduction and tradeoffs that were made. Actual SSDI applied during the DWH oil spill reduced exposures to varying degrees for different VECs. Exposures and relative risks across the ecosystem would have been substantially reduced with more effective SSDI.

Validation of oil fate and mass balance for the Deepwater Horizon oil spill: Evaluation of water column partitioning.

Model predictions of oil transport and fate for the 2010 Deepwater Horizon oil spill (Gulf of Mexico) were compared to field observations and absolute and relative concentrations of oil compounds in samples from 900 to 1400 m depth <11 km from the well. Chemical partitioning analyses using quantitative indices support a bimodal droplet size distribution model for oil released during subsea dispersant applications in June with 74% of the mass in >1 mm droplets that surfaced near the spill site within a few hours, and 1-8% as <0.13 mm microdroplets that remained below 900 m. Analyses focused on 900-1400 m depth <11 km from the well indicate there was substantial biodegradation of dissolved components, some biodegradation in microdroplets, recirculation of weathered microdroplets into the wellhead area, and marine oil snow settling from above 900 m carrying more-weathered particulate oil into the deep plume.

Oil fate and mass balance for the Deepwater Horizon oil spill.

Based on oil fate modeling of the Deepwater Horizon spill through August 2010, during June and July 2010, ~89% of the oil surfaced, ~5% entered (by dissolving or as microdroplets) the deep plume (>900 m), and ~6% dissolved and biodegraded between 900 m and 40 m. Subsea dispersant application reduced surfacing oil by ~7% and evaporation of volatiles by ~26%. By July 2011, of the total oil, ~41% evaporated, ~15% was ashore and in nearshore (<10 m) sediments, ~3% was removed by responders, ~38.4% was in the water column (partially degraded; 29% shallower and 9.4% deeper than 40 m), and ~2.6% sedimented in waters >10 m (including 1.5% after August 2010). Volatile and soluble fractions that did not evaporate biodegraded by the end of August 2010, leaving residual oil to disperse and potentially settle. Model estimates were validated by comparison to field observations of floating oil and atmospheric emissions.

Sensitivity of modeled oil fate and exposure from a subsea blowout to oil droplet sizes, depth, dispersant use, and degradation rates.

As part of a Comparative Risk Assessment (CRA) developed and reported previously, oil spill modeling of a hypothetical blowout at 1400 m in the northeastern Gulf of Mexico was performed to evaluate changes in oil exposures with alternative response options, i.e., combinations of mechanical recovery, in-situ burning, surface dispersant application and subsea dispersant injection (SSDI). To assess if conclusions from this study could be extended to other spill scenarios, sensitivities of the predicted oil fate and exposure metrics to location, release depth, oil and gas flow rate, gas content, orifice size, oil droplet size distribution, and biodegradation rates were examined. Results show that the fraction of oil surfacing is highly sensitive to oil droplet size distribution and depth of release. Across the simulations performed, SSDI use reduced oil droplet sizes released, thereby mitigating surface and shoreline oiling, volatile hydrocarbon exposures, and potential surface water column exposures.

Modeling atmospheric volatile organic compound concentrations resulting from a deepwater oil well blowout - Mitigation by subsea dispersant injection.

The atmospheric concentrations of volatile organic compounds (VOCs) generated by surface slicks during an oil spill have not been extensively studied. We modeled oil transport and fate, air emissions, and atmospheric dispersion of VOCs from a hypothetical deepwater well blowout in De Soto Canyon of the Gulf of Mexico assuming no intervention and use of SubSea Dispersant Injection (SSDI) at the source during three week-long periods representing different atmospheric mixing conditions. Spatially varying time histories of atmospheric VOCs within ~2 km from the release site were estimated. As compared to the no-intervention case, SSDI dispersed the discharged oil over a larger water volume at depth and enhanced VOC dissolution and biodegradation, thereby reducing both the total mass of VOCs released to the atmosphere and the concentration of VOCs within 2 km from the release site. Atmospheric conditions also influenced the VOC concentrations, although to a lesser degree than SSDI.

Comparative Risk Assessment of spill response options for a deepwater oil well blowout: Part 1. Oil spill modeling.

Oil spill model simulations of a deepwater blowout in the Gulf of Mexico De Soto Canyon, assuming no intervention and various response options (i.e., subsea dispersant injection SSDI, in addition to mechanical recovery, in-situ burning, and surface dispersant application) were compared. Predicted oil fate, amount and area of surfaced oil, and exposure concentrations in the water column above potential effects thresholds were used as inputs to a Comparative Risk Assessment to identify response strategies that minimize long-term impacts. SSDI reduced human and wildlife exposure to volatile organic compounds; dispersed oil into a large water volume at depth; enhanced biodegradation; and reduced surface water, nearshore and shoreline exposure to floating oil and entrained/dissolved oil in the upper water column. Tradeoffs included increased oil exposures at depth. However, since organisms are less abundant below 200 m, results indicate that overall exposure of valued ecosystem components was minimized by use of SSDI.

Application of an Integrated Blowout Model System, OILMAP DEEP, to the Deepwater Horizon (DWH) Spill.

OILMAP DEEP, an integrated system of models (pipeline release, blowout plume, dispersant treatment, oil droplet size distribution, and fountain and intrusion), was applied to the Deepwater Horizon (DWH) oil spill to predict the near field transport and fate of the oil and gas released into the northeastern Gulf of Mexico. The model included multiple, time dependent releases from both the kink and riser, with the observed subsurface dispersant treatment, that characterized the DWH spill and response. The blowout model predictions are in good agreement with the available observations for plume trapping height and the major characteristics of the intrusion layer. Predictions of the droplet size distribution are in good agreement with the limited in situ Holocam observations. Model predictions of the percentage of oil retained in the intrusion layer are consistent with independent estimates based on field observations.

Development of a unified oil droplet size distribution model with application to surface breaking waves and subsea blowout releases considering dispersant effects.

An oil droplet size model was developed for a variety of turbulent conditions based on non-dimensional analysis of disruptive and restorative forces, which is applicable to oil droplet formation under both surface breaking-wave and subsurface-blowout conditions, with or without dispersant application. This new model was calibrated and successfully validated with droplet size data obtained from controlled laboratory studies of dispersant-treated and non-treated oil in subsea dispersant tank tests and field surveys, including the Deep Spill experimental release and the Deepwater Horizon blowout oil spill. This model is an advancement over prior models, as it explicitly addresses the effects of the dispersed phase viscosity, resulting from dispersant application and constrains the maximum stable droplet size based on Rayleigh-Taylor instability that is invoked for a release from a large aperture.