The research presents a multisite annual streamflow generation model that combines the Generalized Linear Model (GLM), for determining the temporal structure, with copulas, for modelling the spatial dependence joint distributions. The performance of the GLM-Copula model was verified by comparing its ability to preserve historical features and simulate drought events with the multivariate auto regressive moving average (ARMA) model and the copula autoregressive (COPAR) model. The statistical measures adopted for the models’ performance evaluation include summary statistics (mean, standard deviation, maximum, minimum and skewness coefficient), temporal and spatial correlation, simulation of drought conditions (maximum number of years under drought condition) and copula entropy as a nonlinear measure of total association. The combined GLM-Copula model’s main advantages are that (i) it does …
%0 Journal Article
%1 porto2021copula
%A Porto, Victor Costa
%A de Assis de Souza Filho, Francisco
%A Carvalho, Taís Maria Nunes
%A de Carvalho Studart, Ticiana Marinho
%A Portela, Maria Manuela
%D 2021
%I Elsevier
%J Journal of Hydrology
%K imported topic_earthenvironment
%P 126226
%T A GLM copula approach for multisite annual streamflow generation
%V 598
%X The research presents a multisite annual streamflow generation model that combines the Generalized Linear Model (GLM), for determining the temporal structure, with copulas, for modelling the spatial dependence joint distributions. The performance of the GLM-Copula model was verified by comparing its ability to preserve historical features and simulate drought events with the multivariate auto regressive moving average (ARMA) model and the copula autoregressive (COPAR) model. The statistical measures adopted for the models’ performance evaluation include summary statistics (mean, standard deviation, maximum, minimum and skewness coefficient), temporal and spatial correlation, simulation of drought conditions (maximum number of years under drought condition) and copula entropy as a nonlinear measure of total association. The combined GLM-Copula model’s main advantages are that (i) it does …
@article{porto2021copula,
abstract = {The research presents a multisite annual streamflow generation model that combines the Generalized Linear Model (GLM), for determining the temporal structure, with copulas, for modelling the spatial dependence joint distributions. The performance of the GLM-Copula model was verified by comparing its ability to preserve historical features and simulate drought events with the multivariate auto regressive moving average (ARMA) model and the copula autoregressive (COPAR) model. The statistical measures adopted for the models’ performance evaluation include summary statistics (mean, standard deviation, maximum, minimum and skewness coefficient), temporal and spatial correlation, simulation of drought conditions (maximum number of years under drought condition) and copula entropy as a nonlinear measure of total association. The combined GLM-Copula model’s main advantages are that (i) it does …},
added-at = {2024-11-29T11:56:28.000+0100},
author = {Porto, Victor Costa and de Assis de Souza Filho, Francisco and Carvalho, Taís Maria Nunes and de Carvalho Studart, Ticiana Marinho and Portela, Maria Manuela},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/23f6444ecd587173a00d84bfbf7263fac/joum576e},
citation = {Journal of Hydrology 598, 126226, 2021},
interhash = {aa15af6028d468080012c042b7c8ede4},
intrahash = {3f6444ecd587173a00d84bfbf7263fac},
journal = {Journal of Hydrology},
keywords = {imported topic_earthenvironment},
pages = 126226,
publisher = {Elsevier},
timestamp = {2024-11-29T11:56:28.000+0100},
title = {A GLM copula approach for multisite annual streamflow generation},
volume = 598,
year = 2021
}
