Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/14555
Title: Discrimination of water quality monitoring sites in River Vouga using a mixed-effect state space model
Author: Costa, Marco
Monteiro, Magda
Keywords: Water quality assessment
State space modeling
Kalman smoother
Classification
Structural components
River Vouga
Issue Date: 2016
Publisher: Springer Berlin Heidelberg
Abstract: The surface water quality monitoring is an important concern of public organizations due to its relevance to the public health. Statistical methods are taken as consistent and essential tools in the monitoring procedures in order to prevent and identify environmental problems. This work presents the study case of the hydrological basin of the river Vouga, in Portugal. The main goal is discriminate the water monitoring sites using the monthly dissolved oxygen concentration dataset between January 2002 and May 2013. This is achieved through the extraction of trend and seasonal components in a linear mixed-effect state space model. The parameters estimation is performed with both maximum likelihood method and distribution-free estimators in a two-step procedure. The application of the Kalman smoother algorithm allows to obtain predictions of the structural components as trend and seasonality. The water monitoring sites are discriminated through the structural components by a hierarchical agglomerative clustering procedure. This procedure identified different homogenous groups relatively to the trend and seasonality components and some characteristics of the hydrological basin are presented in order to support the results.
Peer review: yes
URI: http://hdl.handle.net/10773/14555
DOI: 10.1007/s00477-015-1137-y
ISSN: 1436-3240
Appears in Collections:ESTGA - Artigos

Files in This Item:
File Description SizeFormat 
477_2015_1137_Author_prova.pdftexto2.62 MBAdobe PDF    Request a copy
CostaMonteiroSERRA2015.pdf1.58 MBAdobe PDFView/Open


FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpace
Formato BibTex MendeleyEndnote Degois 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.