General NOAA Operational Modeling Environment Research Articles

Utilizing Numerical Models and GIS to Enhance Information Management for Oil Spill Emergency Response and Resource Allocation in the Taiwan Waters

This study aims to establish a comprehensive workflow for developing emergency response plans for both actual and scenario oil spill incidents in the Taiwan waters while addressing the resource allocation for oil spill containment as well. This workflow comprises two vital components. The first component involves the integration of numerical tools and observational data, which includes the incorporation of wind data from sources such as the National Centers for Environmental Prediction (NCEP) or meteorological stations. Additionally, it incorporates ocean current data simulated by the semi-implicit cross-scale hydroscience integrated system model (SCHISM) into the general NOAA operational modeling environment (GNOME) model, which is a new approach for this purpose. In order to assess the efficacy of this component, two distinct case studies were conducted. The first case study focused on an incident in a northern coastal area of Taiwan under open sea conditions, whereas the second case study examined an incident within a major commercial harbor in central Taiwan. The second component of this workflow involves creating oil risk maps by integrating the results from the first component with specific geographical factors into Google Earth. These oil risk maps serve multiple purposes. They offer real-time information to emergency response commanders regarding oil spill hazard prediction, and they also enable the effective development of emergency response strategies and disposal plans for potential oil spill incidents. This is achieved by generating risk maps for various scenarios using the approach outlined in the first component. Additionally, these maps assist in the assessment and planning of resource allocation for oil containment.

Simulation of Oil Spill Trajectory and Fate at the Southern Entrance of the Suez Canal, Red Sea, Egypt

The Suez Canal suffers from heavy maritime traffic, especially oil tankers, due to its strategic location between the Mediterranean and the Red Sea. As a result, it is prone to accidental oil spills, which might obstruct the maritime lane via the canal and severely harm the marine and coastal ecosystems. This study aims to forecast an oil spill trajectory and fate under the influence of different wind regimes using the General NOAA Operational Modeling Environment (GNOME) and the Automated Data Inquiry for Oil Spills (ADIOS2) models to define the potentially affected regions. Hence, four scenarios were simulated, assuming a spill of one thousand metric tons of Arabian light crude oil into the seawater about two kilometers from the Suez Canal’s southern entrance. The results highlight that wind direction and sea currents substantially affect the movement of oil spills. The trajectory maps show that the north-west wind forces the spilled oil to move toward the southeast direction, threatening the navigation lane through the Suez Canal and about 38 km of beaches south of the canal, which has several vital projects such as the Ayoun Mousse power plant and a lot of resorts. In the case of northern winds, the oil moved south in the center of the Gulf, which may allow response teams more time to clean up the spill. However, in the case of north-east winds, the oil drifted southwesterly and threatened the Green Island and western shores of the Gulf, which has many tourist villages. About a quarter of the oil evaporated, and more than two-thirds of the oil emulsified in all four scenarios. For the first time, this study has provided an understanding of oil spill forecasting and trajectory modeling for the Suez Canal’s southern entrance. Also, it can be considered a prediction tool for Egypt’s policymakers and Suez Canal Authority (SCA) to develop adequate and practical strategies to mitigate crude oil spill consequences.

Prediction of Oil Spill Trajectory on the Ocean Surface Using Mathematical Modeling

A simplistic mathematical model based on the law of motion, for predicting oil spill trajectory on the ocean surface utilizing random walk technique is proposed in this paper. Validation of the proposed model is performed by comparing results with the General NOAA Operational Modeling Environment (GNOME) model and the available set of periodic Sentinel -1 Synthetic Aperture Radar (SAR) images of the contingency location (Corsica oil spill incident in the Mediterranean Sea). SAR images are processed for speckle noise removal, dark spot detection, feature extraction and classification of dark spots as oil spills and look-alikes for suitability of comparison. The accuracy of prediction is evaluated using Centroid Skill Score (CSS) metric and is compared with that of the prediction results from MEDSLIK – II model. The results of proposed model are found to be in good agreement with available SAR images. The simulation also showed that using an hourly wind and ocean current data on the study region, more accurate prediction of the trajectory is possible.

A cooperative control framework of multiple unmanned aerial vehicles for dynamic oil spill cleanup

Oil spills within the marine environment are undesirable events caused by unavoidable economic activities of huge sea lane traffics. A tremendous effort has been made to tackle this problem within academia and industries; among them, the concept of autonomous vehicles for oil spill combating seems to provide a promising solution. This paper mainly proposes a cooperative deployment framework for unmanned aerial vehicles (UAVs) to perform oil spill cleanup missions with dispersant spraying. An appropriate oil density function is introduced by applying a Gaussian mixture model based on NOAA’s advanced oil spill model (General NOAA Operational Modeling Environment). UAVs are then deployed to cover oil spills for spraying operations. This deployment problem is formulated as a coverage problem based on centroidal Voronoi tessellation to determine UAVs’ optimal location. By transforming the coverage control problem into a target tracking one, an Integral Terminal Super Twisting Sliding Mode Control is provided to drive the UAVs to the optimal configuration. Furthermore, a novel spraying adjustment strategy is also designed to target the oil spills more accurately at the appropriate dosage. The effectiveness of the proposed framework is studied through a case study in the Abuzar oil field in the Persian Gulf. The results verify the performance of the cooperative oil spill cleanup framework in conjunction with advanced oil spill modeling. Moreover, it is concluded that the oil spill can be more effectively dispersed if the proposed spraying adjustment strategy is implemented.

Simulating the Trajectory and Biomass Growth of Free-Floating Macroalgal Cultivation Platforms along the U.S. West Coast

Trajectory tracking and macroalgal growth models were coupled to support a novel macroalgae-harvesting concept known as the Nautical Off-shore Macroalgal Autonomous Device (NOMAD). The NOMAD consists of 5 km long carbon-fiber longlines that are seeded and free float southward along the U.S. West Coast for approximately 3 months before harvesting off the California coast, taking advantage of favorable environmental conditions. The trajectory and macroalgal growth models were applied to answer planning questions pertinent to the techno-economic analysis such as identifying the preferred release location, approximate pathway, timing until harvest, and estimated growth. Trajectories were determined with the General NOAA Operational Modeling Environment (GNOME) model, using 11 years of current and wind data, determining probabilities by running nearly 40,000 Monte Carlo simulations varying the start time and location. An accompanying macroalgal growth model was used to estimate the growth of macroalgae based on the trajectory tracks and environmental forcing products, including light, temperature and nutrients. Model results show that NOMAD lines transit south in the months of April to September due to seasonal currents, taking approximately 3 months to reach Southern California. During transit, NOMAD lines are dispersed but typically avoid beaching or passing through marine sanctuaries. NOMAD lines can yield up to 30 kg wet weight per meter of cultivation line.

Oil spill trajectory prediction with high-resolution ocean currents

ABSTRACT Simulated ocean currents from ocean circulation models along with the surface winds are generally used to force an oil spill trajectory model. Ocean circulation is a key factor in determining the drift of the spilled marine pollutants. The simulations of the drift pattern of spilled oil, when forced by the ocean currents from two ocean models, are presented here. Merchant Vessel (MV) Rak sunk at 72.4865°E, 18.7715°N, on 4 August 2011. As per the information from Indian Coast Guard, approximately 122.5 tons of fuel oil was spilled from the vessel from 5 August 2011 to 12 August 2011. An oil spill trajectory model, General NOAA Operational Modeling Environment (GNOME), was used to simulate the oil drift pattern from MV Rak from 1000 hours of 5 August 2011 to 1300 hours of 12 August 2011. GNOME was forced with winds from European Centre for Medium Range Weather Forecast (ECMWF) and ocean currents from Indian Ocean Forecasting System (INDOFOS) and High-resolution Operational Ocean Forecasting and reanalysis System (HOOFS). We found that the oil drift pattern obtained when forced with ocean currents from HOOFS was in better agreement with the actual track, compared to the one obtained while using INDOFOS currents.

Quantifying exposure levels of coastal facilities to oil spills in Bahrain, Arabian Gulf.

The Arabian Gulf is considered as a hub for global oil industry. Thus the Arabian Gulf marine environment is under permanent threat from oil spills due to oil exploitation, production, and transportation. Oil pollution poses adverse effects on marine environment, society, and economy. Oil spill incidents that occurred in Bahrain caused damage to marine environment and threatened the vital coastal facilities along the coastline of Bahrain. This study determined the exposure levels of coastal facilities in Bahrain to oil spills. The General NOAA Operational Modeling Environment (GNOME) model was validated and applied to hypothetical oil spill scenarios. The modeling results showed that the coastal facilities on the north-eastern coastline are more probable to be hit by oil spills, while those on the northern coastline are susceptible to receive more quantity of oil. The time required for oil to reach the western coastline is shorter compared to the other coastlines. The modeling outcomes can be utilized in contingency planning, setting the protection priorities and allocation and mobilization of response resources in both governmental and private sectors. The implications of the present study could be applied on a regional scale to ensure an integrated response to combat and or minimize oil pollution in the Arabian Gulf.

Simulation of the 2003 Foss Barge - Point Wells Oil Spill: A Comparison between BLOSOM and GNOME Oil Spill Models

The Department of Energy’s (DOE’s) National Energy Technology Laboratory’s (NETL’s) Blowout and Spill Occurrence Model (BLOSOM), and the National Oceanic and Atmospheric Administration’s (NOAA’s) General NOAA Operational Modeling Environment (GNOME) are compared. Increasingly complex simulations are used to assess similarities and differences between the two models’ components. The simulations presented here are forced by ocean currents from a Finite Volume Community Ocean Model (FVCOM) implementation that has excellent skill in representing tidal motion, and with observed wind data that compensates for a coarse vertical ocean model resolution. The comprehensive comparison between GNOME and BLOSOM presented here, should aid modelers in interpreting their results. Beyond many similarities, aspects where both models are distinct are highlighted. Some suggestions for improvement are included, e.g., the inclusion of temporal interpolation of the forcing fields (BLOSOM) or the inclusion of a deflection angle option when parameterizing wind-driven processes (GNOME). Overall, GNOME and BLOSOM perform similarly, and are found to be complementary oil spill models. This paper also sheds light on what drove the historical Point Wells spill, and serves the additional purpose of being a learning resource for those interested in oil spill modeling. The increasingly complex approach used for the comparison is also used, in parallel, to illustrate the approach an oil spill modeler would typically follow when trying to hindcast or forecast an oil spill, including detailed technical information on basic aspects, like choosing a computational time step. We discuss our successful hindcast of the 2003 Point Wells oil spill that, to our knowledge, had remained unexplained. The oil spill models’ solutions are compared to the historical Point Wells’ oil trajectory, in time and space, as determined from overflight information. Our hindcast broadly replicates the correct locations at the correct times, using accurate tide and wind forcing. While the choice of wind coefficient we use is unconventional, a simplified analytic model supported by observations, suggests that it is justified under this study’s circumstances. We highlight some of the key oceanographic findings as they may relate to other oil spills, and to the regional oceanography of the Salish Sea, including recommendations for future studies.

Predicting Surface Oil Transport in California Using a High-Resolution Regional Ocean Modeling System (ROMS) and the National Oceanic and Atmospheric Administration's (NOAA's) Trajectory Analysis Planner (TAP)

The Bureau of Ocean Energy Management (BOEM) and Bureau of Safety and Environmental Enforcement (BSEE) Pacific Region conduct oil spill risk analyses to determine potential impacts to environmental resources. Oil spill trajectory modeling is conducted to predict the movement and fate of spilled oil, if a spill occurred, from existing offshore oil and gas operations in southern California. To improve BOEM and BSEE Pacific Region's ability to conduct oil spill risk analyses for southern California, BOEM partnered with the University of California, Los Angeles (UCLA) to run a multi-year hind cast (re-analysis) of winds, waves, and currents along the coast of California. UCLA created a high-resolution (1 km) ROMS hind cast for the 10 year period 2004–2013 from Morro Bay, California to the border with Mexico. The project was conducted in three phases: (1) Surface winds were calculated at high horizontal and temporal resolution and validated using existing datasets; (2) A wave model was forced by the wind model results and validated through in situ measurements; and (3) The ocean model was run at high resolution and includes temperature, salinity, and currents; it assimilated in situ data and was forced by the hind cast atmospheric model results. BOEM is subsequently partnering with NOAA, to utilize the surface currents and winds from the ROMS hind cast analysis with NOAA's General NOAA Operational Modeling Environment (GNOME) to produce multiple trajectories for NOAA's TAP. Using realistic oil spill scenarios over a range of different regional oceanographic regimes (such as upwelling, relaxation, and eddy-driven flow), TAP will calculate the probabilities of oil contacting parcels of water and shoreline were any oil to spill from southern California oil platforms. This will enable analysts to understand where an oil spill may travel, how long it could take to get there, and the likelihood of spilled oil contacting their resource area. An online TAP viewer with the GNOME-generated data from this study will be publicly available along with the ROMS hind cast data for oil spill response planning along with other oceanographic modeling needs.

Numerical modelling of oil spill in New York Bay

Abstract New York Bay is one of the most important transition regions of ships trading to east America. The region plays an important role in the commerce of the New York metropolitan area. The area is surrounded with the coasts that have various levels of environmental sensitivity. The area accommodates high diversity of native ecosystems and species that are rather vulnerable in case of oil spill. Thus getting well informed about the likelihood, or fate, of oil spills around this region is of great importance so that proactive measures can be taken. The purpose of this study is to investigate the oil spill and predict the future accidents likely to be encountered around the Bay of New York. Two trajectory models have been conducted for the study. ADIOS (Automated Data Inquiry for Oil Spills), has been conducted for natural degradation calculations, and, GNOME (General NOAA Operational Modeling Environment), has been conducted for surface spread simulation. The results gained through these efforts are hoped to be useful for many organizations dealing with oil spill response operations and contribute to an effective and efficient coordination among the relevant institutions.

Spatial and Temporal Variations of Oil Spills in the North Sea Observed by the Satellite Constellation of TerraSAR-X and TanDEM-X

This study investigated the spatial and temporal variations of two groups of oil slicks with similar features that were observed in the North Sea by spaceborne synthetic aperture radar (SAR) TerraSAR-X (TSX) and TanDEM-X (TDX) within 13 h of each other, which were operating in the satellite constellation. Based on the SAR observations and the General NOAA Operational Modeling Environment (GNOME) simulations of the oil trajectories, it is unlikely that the oil spills observed by TSX on August 21, 2012 entirely drifted from the oil spills observed by TDX on August 20. Rather, the oil slicks observed after 13 h were likely composed of two parts. One part was the new oil spills that started to leak sometime after the first SAR acquisition on August 20 and that were subsequently observed on August 21. The other part was the older oil spills that had drifted from the original oil slicks observed on August 20 by TDX. The fast weathering of light crude oil and the mixture of oil and water produced in the Forties platforms should contribute to the rapid dispersion and dissipation of the previously observed oil slicks. The findings of this study contribute to our understanding of the life history of oil spill on the sea surface around offshore drilling platforms.

Temporal variability of marine debris deposition at Tern Island in the Northwestern Hawaiian Islands

A twenty-two year record of marine debris collected on Tern Island is used to characterize the temporal variability of debris deposition at a coral atoll in the Northwestern Hawaiian Islands. Debris deposition tends to be episodic, without a significant relationship to local forcing processes associated with winds, sea level, waves, and proximity to the Subtropical Convergence Zone. The General NOAA Operational Modeling Environment is used to estimate likely debris pathways for Tern Island. The majority of modeled arrivals come from the northeast following prevailing trade winds and surface currents, with trajectories indicating the importance of the convergence zone, or garbage patch, in the North Pacific High region. Although debris deposition does not generally exhibit a significant seasonal cycle, some debris types contain considerable 3cycle/yr variability that is coherent with wind and surface pressure over a broad region north of Tern.

Modeling of oil spill beaching along the coast of the Bohai Sea, China

On June 4 and 17, 2011, two separate oil spill accidents occurred at platforms B and C of the Penglai 19-3 oilfield located in the Bohai Sea, China. Based on the initial oil spill locations detected from the first available Synthetic Aperture Radar (SAR) image acquired on June 11, 2011, we performed a numerical experiment to simulate the potential oil spill beaching area with the General NOAA Operational Modeling Environment (GNOME) model. The model was driven by ocean surface currents from an operational ocean model (Navy Coastal Ocean Model) and surface winds from operational scatterometer measurements (the Advanced Scatterometer). Under the forcing of wind and ocean currents, some of the oil spills reached land along the coast of Qinhuangdao within 12 days. The results also demonstrate that the ocean currents are likely to carry the remaining oil spills along the Bohai coast towards the northeast. The predicted oil spill beaching area was verified by reported in-situ measurements and former studies based on MODIS observations.

Characterization of the Seasonal Circulation Patterns and Its Application on Oil Spill Transport in the Northwestern Continental Shelf of India

We implemented the Princeton Ocean Model to study the seasonal circulation patterns in the Gulf of Khambhat and surrounding oceans on the northwestern continental shelf of India. Simulated currents are used in General NOAA Operational Modeling Environment to track a past oil spill event in this region. The model's performance is evaluated against the Synthetic Aperture Radar (SAR) and in situ measurements. Mean currents, computed by subtracting tidal components from the simulated currents, are used together with satellite images of Chlorophyll-a to describe spatial patterns of the circulation. Mean-flow patterns inside the gulf are characterized with strong along-channel flow during southwest monsoon and spring seasons, which are weak during winter and autumn seasons. On the proximity of the gulf mouth currents are northwestward throughout the year except the southwest monsoon when the circulations are southwestward. Coastal boundary currents parallel to the 60 m isobath are prominent during the inter-monsoon and weak during the monsoon periods. Slope currents, near the shelf-break, are strong during southwest monsoon and spring periods. Numerical experiments suggest that ocean current is the main driver of the net transport of spilled oil in this region and other factors such as direct wind drift play negligible role.

Monitoring of Oil Spill Trajectories With COSMO-SkyMed X-Band SAR Images and Model Simulation

The Shell North Sea Gannet Alpha platform oil spill accident occurred on August 10, 2011. This was the largest oil spill accident in United Kingdom waters in the last decade. The spills were observed on four COSMO-SkyMed (CSK) X-band synthetic aperture radar (SAR) images acquired between August 17 and 22, 2011, with revisit time from 11 h to 3 days between the SAR acquisitions. The areas of oil slicks were extracted from SAR images using an existing image classification and segmentation algorithm. It was found that the oil slicks moved toward the southwest with slick size enlarging from 3.69 to 62.01 km2 in the first 24 h between the first and second SAR acquisitions. We tracked the oil spill trajectories using the General NOAA Operational Modeling Environment (GNOME) oil-drifting model. The 6-hourly surface wind fields from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA) Interim products and the 3-hourly ocean surface current fields from the Navy Coastal Ocean Model (NCOM) global operational model were used to drive the GNOME model. The simulated oil slick movement was in good agreement with that observed by the CSK SAR images. Moreover, the simulation showed that the movement of oil spills was dominated by the surface winds in the North Sea.

Integrating Google Maps/Earth Into an Automated Oil Spill Forecast System

AbstractAn automated method for visualizing oil spill forecasts using Google Maps and Google Earth has been integrated into a Hydrodynamic and Oil Spill Python (HyosPy) modeling system. HyosPy downloads wind and tide observations and forecasts, runs a hydrodynamic model (the Semi-Implicit Eulerian Lagrangian Finite Element), links to an oil spill model (General NOAA Operational Modeling Environment), and visualizes the predicted spill trajectories. Using object-oriented approaches with Python code, HyosPy can run multiple instances of the hydrodynamic and oil spill models to provide a set of multiple predicted spill tracks controlled by different wind and tide forecasts. Automation of HyosPy allows the hydrodynamic model to be continuously running on a server so that hydrodynamic forecasts are immediately available in the event of a spill. Once the size, location, and time of the oil spill are provided to the system, no further human intervention is necessary. Google Maps/Earth visualization methods employ JavaScript tools and Keyhole Markup Language files to provide rapid display and animation in Web browsers of Java-capable devices. HyosPy is designed with a loosely coupled architecture to permit easy update and adaptation to different models and data sources.

Utilization of the Northern Gulf Operational Forecast System to Predict Trajectories of Surface Oil from a Persistent Source Offshore of the Mississippi River Delta

ABSTRACT In this paper, we demonstrate the use of a new operational, unstructured-grid hydrodynamic model within the oil spill trajectory model GNOME (the General NOAA Operational Modeling Environment) to examine the transport of surface oil from a known source approximately 10 miles offshore of the Mississippi River Delta. At this location, a cluster of wells and/or contaminated sediments have been persistently leaking small amounts of oil since they were damaged in 2004. Slicks associated with this source are frequently detected in satellite imagery analysis, which indicates they are often oriented in the along isobath direction with typical dimensions of 0.5–2 km by 10–30 km varying with wind conditions. The Northern Gulf of Mexico Operation Forecast System (NGOFS) has recently been deployed by NOAA and includes this region. The underlying hydrodynamic model is an unstructured grid finite-volume model which allows variable grid resolution ranging from 10 km offshore to ~600 m near the coastline. Unstructured grid models are ideally suited for coastal areas as they allow flexible resolution to resolve complex bathymetry and coastlines. However, large model domains combined with high grid resolution can provide a challenge for operational trajectory models as sub-setting the model grid is not as straightforward as in the structured grid case. The utility of any hydrodynamic model for emergency response depends not only on its accuracy, but on the trajectory modeler's ability to access and use the information in a timely manner. As part of this study, we have developed tools to allow the NGOFS results (in addition to other unstructured grid models) to be readily available to GNOME users. Using output from the NGOFS in GNOME, a one year modeled simulation was run in which surface particles were released continuously from the location of the damaged wells. Predicted trajectories of modeled particles less than ~24-hours in age compare qualitatively well with the satellite observations.

Numerical Study of the Oil Spill Trajectory in Bohai Sea, China

Sixteen numerical experiments are conducted using the General NOAA Operational Modeling Environment (GNOME) to numerically study the oil spill trajectory in the Bohai Sea, China, for the purpose of providing information for the oil cleanup and disaster mitigation. High resolution coastline and topography data investigated by China's 908 Program are used to accurately describe the regional geographic feature of the Bohai Sea. Currents and waves required by GNOME are generated by the Hybrid Coordinate Ocean Model and Simulating Wave Nearshore, respectively. Experimental results show that oil spilled in different seasons and at different locations will result in completely different spilling trajectories, traveling distances, and polluting areas. Knowing that information comprehensively is vital to pollution control. Another important goal of this work is to provide users with simulated oil spill trajectory information through China Digital Ocean Prototype System (CDOPS), a grand marine information platform for managing, displaying, and public sharing of the data investigated by the China 908 Program. Users can obtain the trajectory, spreading, and potential impact area of the spilled oil through the oil spill module in CDOPS.

Satellite observations and modeling of oil spill trajectories in the Bohai Sea

On June 4 and 17, 2011, separate oil spill accidents occurred at two oil platforms in the Bohai Sea, China. The oil spills were subsequently observed on different types of satellite images including SAR (Synthetic Aperture Radar), Chinese HJ-1-B CCD and NASA MODIS. To illustrate the fate of the oil spills, we performed two numerical simulations to simulate the trajectories of the oil spills with the GNOME (General NOAA Operational Modeling Environment) model. For the first time, we drive the GNOME with currents obtained from an operational ocean model (NCOM, Navy Coastal Ocean Model) and surface winds from operational scatterometer measurements (ASCAT, the Advanced Scatterometer). Both data sets are freely and openly available. The initial oil spill location inputs to the model are based on the detected oil spill locations from the SAR images acquired on June 11 and 14. Three oil slicks are tracked simultaneously and our results show good agreement between model simulations and subsequent satellite observations in the semi-enclosed shallow sea. Moreover, GNOME simulation shows that the number of ‘splots’, which denotes the extent of spilled oil, is a vital factor for GNOME running stability when the number is less than 500. Therefore, oil spill area information obtained from satellite sensors, especially SAR, is an important factor for setting up the initial model conditions.

Development of a Global Oil Spill Modeling System

This paper describes the development of an oil spill modeling system that is operational on a global scale and can be used for both real-time response, forecast simulations and probabilistic risk analysis based on climatological wind and ocean current data. For ocean and estuarine spills, the system makes use of the General NOAA Operational Modeling Environment (GNOME) oil spill model, Trajectory Analysis Planner and the Automated Data Inquiry for Oil Spills weathering model. Hydrodynamic and meteorological data is obtained from the US Navy and National Oceanic and Atmospheric Administration. Data access is provided through the Naval Oceanographic Office, the Fleet Numerical Meteorological and Oceanographic Center and the GNOME Online Oceanographic Data Server. For riverine spills, the GeoSpatial Stream Flow Model and the Incident Command Tool for Drinking Water Protection are used to respectively, build river networks with associated flows and velocities and, transport and disperse oil spill contamination downstream. Case study examples are presented for both forecast simulations and probabilistic risk analysis.