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.
The Incident Command Tool for Drinking Water Protection (ICWater) provides real‐time assessments of the travel and dispersion of contaminants in streams and rivers. It is structured around the RiverSpill model which has been enhanced to make use of the 1:100 000 scale National Hydrography Dataset Plus, Version 1.0 (NHDPlusV1). NHDPlusV1 is a hydrologically connected river network that contains over 3 million reach segments in the United States. This allows for both downstream and upstream tracing (which serves in forensic analysis). Mean flow and velocity have been calculated by the US Geological Survey (USGS) and Environmental Protection Agency (EPA) for each reach. These mean values are updated by flow from web accessible real‐time gauging stations. Example databases available within ICWater include: dams, reservoirs, water supplies, gauges, municipal and industrial dischargers and transportation networks. A contaminant database is also included which identifies biological, chemical and radiological contaminants and their toxicities. Navigating the river network upstream coupled with mass‐balance calculations from breakthrough curves allows for backtracking of the contamination to determine the origin and source strength.
The integration of three hydraulic GIS (Geographic Information System) applications is presented which represent the water infrastructures of cities and urban areas and US streams and rivers. The water infrastructures include drinking water distribution systems, wastewater collection systems and source water. The National Research Council[1] states that problems dealing with the collective behavior of networks such as river systems, water distribution systems and waste water collection systems are complex because they include feedback loops, produce counter-intuitive behaviors and exhibit behaviors that cannot be predicted from the attributes of individual components. A complex system includes all of the above individual components, yet also exhibits emergent collective behavior caused by the interactions among its features. The integration of these applications have been developed for use in planning, response, training and development of monitoring strategies to address potential deliberate or accidental toxic contamination events
Using geographic information system techniques, elevation derived datasets such as flow accumulation, flow direction, hillsope and flow length were used to delineate river basin boundaries and networks. These datasets included both HYDRO1K (based on 1 km resolution DEM) and HydroSHEDs (based on 100 meter Shuttle Radar Topography Mission). Additional spatial data processing of global landuse and soil type data were used to derive grids representing soil depth, texture, hydraulic conductivity, water holding capacity, and curve number. These grids were input to the Geospatial Stream Flow model to calculate overland flow (both travel time and velocity). The model was applied to river basins across several continents to calculate river discharge and velocity based on the use of satellite derived rainfall estimates, numerical weather forecast fields, and geographic data sets describing the land surface. Model output was compared to historical stream gauge observations as a validation step. The stream networks with associated discharge and velocity are used as input to a riverine water contamination model.
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