HyosPy: Texas Bay Oil Spill Probability Maps and Particle Tracks

The Hydrodynamic Oil Spill–Python (HyosPy) system is an integrated modeling framework for predicting oil spill trajectories and generating probability maps. The system combines multiple hydrodynamic and oil spill models, driven by real-time forecast data, and has been tested and validated for Galveston Bay. This report represents the culmination of a decade of work funded by TGLO, beginning in 2009, to develop an advanced simulation system for Texas bays and estuaries.

Use Cases

• Generate oil spill probability maps for emergency response based on the multi-model ensemble approach described.
• Simulate oil particle tracks in coastal estuaries based on hydrodynamic models like SUNTANS, SELFE, and ROMS.
• Evaluate model uncertainty and integrate new scientific mechanics into spill predictions using the HyosPy framework.
• Analyze bay connectivity and the impact of events like Deepwater Horizon or Hurricane Harvey on spill dispersion.

Strengths

• System integrates multiple established models (SUNTANS, SELFE, ROMS, GNOME, TracPy) for ensemble forecasting.
• Framework is designed for operational use with real-time forecast data from web services.
• Development represents a decade of research and testing, specifically validated for Galveston Bay.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and specific file formats are unknown, which may limit suitability assessment.

Provenance

Source

Texas Data Repository Harvested Dataverse

Collection Method

Model outputs and research from the HyosPy integrated modeling system.

Time Range

Research and development began in 2009.

Freshness

Last updated 2024-03-18 06:33:27; freshness should be verified.

Geography

Texas coastal bays and estuaries, with specific testing in Galveston Bay.