A Time Series Model Comparison for Monitoring and Forecasting Water Quality Variables

Magda Monteiro,Marco Costa

doi:10.3390/hydrology5030037

Abstract

The monitoring and prediction of water quality parameters are important tasks in the management of water resources. In this work, the performances of time series statistical models were evaluated to predict and forecast the dissolved oxygen (DO) concentration in several monitoring sites located along the main river Vouga, in Portugal, during the period from January 2002 to May 2015. The models being compared are a regression model with correlated errors and a state-space model, which can be seen as a calibration model. Both models allow the incorporation of water quality variables, such as time correlation or seasonality. Results show that, for the DO variable, the calibration model outperforms the regression model for sample modeling, that is, for a short-term forecast, while the regression model with correlated errors has a better performance for the forecasting h-steps ahead framework. So, the calibration model is more useful for water monitoring using an online or real-time procedure, while the regression model with correlated errors can be applied in order to forecast over a longer period of time.

Highlights

Water quality is routinely assessed in streams, rivers, lakes, and reservoirs, especially when there are significant industrial activities and human populations in these areas
We considered the coefficient of determination R2, the mean square error (MSE), the mean absolute error (MAE), and the mean percentage absolute error (MPAE); in the forecast framework, only considered the last three measures were considered
Since the dissolved oxygen (DO) concentration series has a seasonal behavior, at a preliminary stage, we considered a linear regression model (MI) that accounts for the seasonal behavior of the DO concentration during the year, as well as for the increase in DO concentration that may occur at different rates according to the month

Summary

Introduction

Water quality is routinely assessed in streams, rivers, lakes, and reservoirs, especially when there are significant industrial activities and human populations in these areas. In other contexts, water quality assessment is a process that contributes to environmental and ecosystem monitoring. The analysis and monitoring of water quality through systematic and scientifically established procedures provide important information on the status of these basins, while helping official entities target their decision-making processes toward supported policy options. In a hydrological basin, this information can be used to build an understanding of the dynamic of the basin and how nutrients and other contaminants behave over time, namely, by monitoring both seasonal changes and long-term trends. In the European Union (EU), the management of water resources is regulated by EU directives and their transposition into national legislation.

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Discussion

Conclusion