Predicting seasonal and hydro-meteorological impact in environmental variables modelling via Kalman filtering

Original Paper

Abstract

This study focuses on the potential improvement of environmental variables modelling by using linear state-space models, as an improvement of the linear regression model, and by incorporating a constructed hydro-meteorological covariate. The Kalman filter predictors allow to obtain accurate predictions of calibration factors for both seasonal and hydro-meteorological components. This methodology can be used to analyze the water quality behaviour by minimizing the effect of the hydrological conditions. This idea is illustrated based on a rather extended data set relative to the River Ave basin (Portugal) that consists mainly of monthly measurements of dissolved oxygen concentration in a network of water quality monitoring sites. The hydro-meteorological factor is constructed for each monitoring site based on monthly precipitation estimates obtained by means of a rain gauge network associated with stochastic interpolation (kriging). A linear state-space model is fitted for each homogeneous group (obtained by clustering techniques) of water monitoring sites. The adjustment of linear state-space models is performed by using distribution-free estimators developed in a separate section.

Keywords

Hydrological basin Water quality State-space modelling Kalman filter Distribution-free estimation 

Notes

Acknowledgements

The authors would like to thank to Eng. Pimenta Machado from the Portuguese Regional Directory for the Northern Environment and Natural Resources, and to Eng. Cláudia Brandão from the Portuguese Institute of Water, for sharing their skills and experiences and for supplying the monitored data. A. Manuela Gonçalves acknowledges the financial support provided by the Research Centre of Mathematics of the University of Minho through the FCT Pluriannual Funding Program.

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  1. 1.Departamento de Matemática e AplicaçõesUniversidade do MinhoGuimarãesPortugal
  2. 2.CMAT-Centro de Matemática da Universidade do MinhoBragaPortugal
  3. 3.Escola Superior de Tecnologia e Gestão de ÁguedaUniversidade de AveiroÁguedaPortugal
  4. 4.CMAF-Centro de Matemática e Aplicações Fundamentais da Universidade de LisboaLisboaPortugal

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