Application of DDDAS in marine oil spill management: A new framework combining multiple source remote sensing monitoring and simulation as a symbiotic feedback control system

Marine oil spills is one of the most serious sea pollution which has a horrible effect on environment, economy, and quality of life for coastal inhabitants. How to reduce the risk of oil spill disasters has become one of the principal problems faced with marine environment management. Oil spill observation and spill processes simulation are two main parts for oil spill accident controlling and management. Traditionally, the oil spill information detection and spill simulation is disjoined without any feedback. The modeling approach is all conducted with fixed structure and static data input while the observation system is always static with fixed monitoring scheme. In such a circumstance, neither the observation system nor the simulation can provide highly accurate information. This paper propose a new framework combining oil spill monitoring and simulation as a symbiotic feedback control system based on the theory of Dynamic Data Drive Application System (DDDAS), a new paradigm dynamically integrated simulations, measurements, and applications. The numerical oil spill model can accepts real time data from remote sensing monitoring which assure modeling a more accurate and more reliable outcomes. Multiple simulations will be executed with different remote sensing monitoring scheme and the feedback from simulation guide and determine how to gather the data. For mathematical modeling of the DDDAS based marine oil spill management system, we built a multi-stage optimization model. Such system could promise more accurate prediction and more reliable outcomes with real time oil spill input, which will improve modeling technologies, advance prediction capabilities of simulation systems, and enhance oil spill monitoring.