000061327 001__ 61327
000061327 005__ 20170519135025.0
000061327 0247_ $$2doi$$a10.1016/j.jhydrol.2011.01.049
000061327 0248_ $$2sideral$$a72541
000061327 037__ $$aART-2011-72541
000061327 041__ $$aeng
000061327 100__ $$0(orcid)0000-0002-7974-7435$$aAbaurrea, J.$$uUniversidad de Zaragoza
000061327 245__ $$aTrend analysis of water quality series based on regression models with correlated errors
000061327 260__ $$c2011
000061327 5060_ $$aAccess copy available to the general public$$fUnrestricted
000061327 5203_ $$aThis work proposes a methodology for characterizing the time evolution of water quality time series taking into consideration the inherent problems that often appear in this type of data such as non-linear trends, series having missing data, outliers, irregular measurement patterns, seasonal behavior, and serial correlation. The suggested approach, based on regression models with a Gaussian autoregressive moving average (ARMA) error, provides a framework where those problems can be dealt with simultaneously. Also the model takes into account the effect of influential factors, such as river flows, water temperature, and rainfall.
The proposed approach is general and can be applied to different types of water quality series. We applied the modeling framework to four monthly conductivity series recorded at the Ebro river basin (Spain). The results show that the model fits the data reasonably well, that time evolution of the conductivity series is non-homogeneous over the year and, in some cases, non-monotonic. In addition, the results compared favorably over those obtained using simple linear regression, pre-whitening, and trend-free-pre-whitening techniques.
000061327 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000061327 590__ $$a2.656$$b2011
000061327 591__ $$aENGINEERING, CIVIL$$b5 / 118 = 0.042$$c2011$$dQ1$$eT1
000061327 591__ $$aWATER RESOURCES$$b4 / 78 = 0.051$$c2011$$dQ1$$eT1
000061327 591__ $$aGEOSCIENCES, MULTIDISCIPLINARY$$b25 / 170 = 0.147$$c2011$$dQ1$$eT1
000061327 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000061327 700__ $$0(orcid)0000-0002-0174-789X$$aAsín, J.$$uUniversidad de Zaragoza
000061327 700__ $$0(orcid)0000-0002-9052-9674$$aCebrián, A. C.$$uUniversidad de Zaragoza
000061327 700__ $$aGarcía-Vera, M.A.
000061327 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDepartamento de Métodos Estadísticos$$cEstadística e Investigación Operativa
000061327 773__ $$g400, 3-4 (2011), 341-352$$pJ. hydrol.$$tJOURNAL OF HYDROLOGY$$x0022-1694
000061327 8564_ $$s1060169$$uhttp://zaguan.unizar.es/record/61327/files/texto_completo.pdf$$yPostprint
000061327 8564_ $$s54781$$uhttp://zaguan.unizar.es/record/61327/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000061327 909CO $$ooai:zaguan.unizar.es:61327$$particulos$$pdriver
000061327 951__ $$a2017-05-19-13:16:35
000061327 980__ $$aARTICLE