  Turbidity is commonly monitored as an important water quality index. Human
activities, such as dredging and dumping operations, can disrupt turbidity
levels and should be monitored and analyzed for possible effects. In this
paper, we model the variations of turbidity in Dublin Bay over space and time
to investigate the effects of dumping and dredging while controlling for the
effect of wind speed as a common atmospheric effect. We develop a novel Vector
Auto-Regressive Conditional Heteroskedasticity (VARCH) approach to modelling
the dynamical behaviour of turbidity over different locations and at different
water depths. We use daily values of turbidity during the years 2017-2018 to
fit the model. We show that the results of our fitted model are in line with
the observed data and that the uncertainties, measured through Bayesian
credible intervals, are well calibrated. Furthermore, we show that the daily
effects of dredging and dumping on turbidity are negligible in comparison to
that of wind speed.
