Author(s): R. Rao; V. Babovic
Linked Author(s): Vladan Babovic
Keywords: No Keywords
Abstract: The shallow waters and narrow straits around Singapore cater to one third the navigation traffic in the world. Hence, accurate prediction of water level and currents in the region is most important part of any maritime decision support system aiming optimal ship routing, port and coastal management. The main challenge is in understanding and predicting the non-tidal anomalies (sea level anomalies; SLAs and current anomalies) which are characteristics of such narrow straits. A data driven approach based on mutual information theory has been presented here as an investigation tool to unearth the underlying temporal and spatial patterns of SLA in the Singapore region. The analysis is based on the SLA time series data for 17 locations in the region. Average Mutual Information is used to compare the overall SLA signals of different stations. Specific significant SLA events are identified and analyzed for temporal correlations.
Year: 2009