A Bayesian Analysis of Coastal Water Quality

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This project will apply a Bayesian spatial dynamic factor model to study the determinants of coastal water quality and its dependence on environmental conditions. The approach will take advantage of data from the Southern California Coastal Ocean Observing System (SCCOOS) on water quality, temperature, salinity, precipitation, solar radiation, tide cycle, wind, and currents. Product will be a peer-reviewed publication.

 

Project P.I.: 
Sunny Jiang (Civil & Environmental Eng.) & Ivan Jeliazkov (Economics)

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