The Extended Kalman Filter (EKF) as a tool for the assimilation of high frequency water quality data

Abstract

The Extended Kalman Filter (EKF) was applied to the analysis of high frequency field measurements of dissolved oxygen (DO), water temperature, salinity, collected by multiparametric sensors in the lagoon of Venice. This paper focuses on the practical aspects of the implementation of the EKF as a data assimilation technique and does not deal with the problems associated with the identification of the model. In this regard, the EKF has proved to be a useful tool for the updating of the estimates of the parameters of a simple DO-chlorophyll model, which can be used for linking the high frequency data to meteorological forcings, such as solar radiation and wind, and to other low frequency measurements of water quality parameters, such as the concentrations of Chlorophyll a and nutrients. The model can subsequently be used as a tool for checking the consistency of all this data, and may also be employed for controlling the quality of the data collected by the multiparametric sensors.