Vector Time Series Modelling of Turbidity in Dublin Bay

TL;DR

This paper models turbidity variations in Dublin Bay using a novel VARCH approach to analyze the effects of dredging, dumping, and wind speed, providing insights into water quality dynamics.

Contribution

Introduces a new VARCH model for spatial-temporal turbidity analysis, accounting for environmental factors and human activities in Dublin Bay.

Findings

Wind speed significantly affects turbidity levels.

Dredging and dumping have negligible effects compared to wind.

Model accurately fits observed turbidity data.

Abstract

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.