HR: 0800h
AN: OS41A-0160    [Abstracts]
TI: A statistical model for water quality predictions from a river discharge using coastal observations
AU: * Kim, S
EM: syongkim@mpl.ucsd.edu
AF: Scripps Institution of Oceanography, 9500 Gilaman Dr., La Jolla, CA 92093-0213, United States
AU: Terrill, E J
EM: eterrill@ucsd.edu
AF: Scripps Institution of Oceanography, 9500 Gilaman Dr., La Jolla, CA 92093-0213, United States
AB: Understanding and predicting coastal ocean water quality has benefits for reducing human health risks, protecting the environment, and improving local economies which depend on clean beaches. Continuous observations of coastal physical oceanography increase the understanding of the processes which control the fate and transport of a riverine plume which potentially contains high levels of contaminants from the upstream watershed. A data-driven model of the fate and transport of river plume water from the Tijuana River has been developed using surface current observations provided by a network of HF radar operated as part of a local coastal observatory that has been in place since 2002. The model outputs are compared with water quality sampling of shoreline indicator bacteria, and the skill of an alarm for low water quality is evaluated using the receiver operating characteristic (ROC) curve. In addition, statistical analysis of beach closures in comparison with environmental variables is also discussed.
UR: http://sdcoos.ucsd.edu/data/particles/IB/
DE: 4251 Marine pollution (0345, 0478)
DE: 4262 Ocean observing systems
SC: Ocean Sciences [OS]
MN: 2007 Fall Meeting