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http://hdl.handle.net/10773/9191
Title: | Predicting seasonal and hydro-meteorological impact in environmental variables modelling via Kalman filtering |
Author: | Gonçalves, A. Costa, Marco |
Keywords: | Hydrological basin Water quality State-space modelling Kalman filter Distribution-free estimation |
Issue Date: | Jul-2013 |
Publisher: | Springer |
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 predic- tors 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. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/9191 |
DOI: | 10.1007/s00477-012-0640-7 |
ISSN: | 1436-3240 |
Appears in Collections: | ESTGA - Artigos |
Files in This Item:
File | Description | Size | Format | |
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GoncalvesCosta2012_04_10.pdf | 1.1 MB | Adobe PDF | View/Open |
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