Bayesian estimation of uncertainty in runoff prediction and the value of data: An application of the GLUE approach Export

@article{citeulike:763789, abstract = {This paper addresses the problem of evaluating the predictive uncertainty of TOPMODEL using the Bayesian Generalized Likelihood Uncertainty Estimation (GLUE) methodology in an application to the small Ringelbach research catchment in the Vosges, France. The wide range of parameter sets giving acceptable simulations is demonstrated, and uncertainty bands are presented based on different likelihood measures. It is shown how the distributions of predicted discharges are non-Gaussian and vary in shape through time and with discharge. Updating of the likelihood weights using Bayes equation is demonstrated after each year of record and it is shown how the additional data can be evaluated in terms of the way they constrain the uncertainty bands. \© American Geophysical Union 1996}, author = {Freer, Jim and Beven, Keith and Ambroise, Bruno}, citeulike-article-id = {763789}, citeulike-linkout-0 = {http://www.agu.org/pubs/crossref/1996/96WR03723.shtml}, journal = {Water Resources Research}, keywords = {glue, hydrology, uncertainty}, number = {7}, pages = {2161--2174}, posted-at = {2006-07-19 01:46:59}, priority = {2}, title = {Bayesian estimation of uncertainty in runoff prediction and the value of data: An application of the GLUE approach}, url = {http://www.agu.org/pubs/crossref/1996/96WR03723.shtml}, volume = {32} }

TY - JOUR ID - citeulike:763789 L3 - citeulike-article-id:763789 N2 - This paper addresses the problem of evaluating the predictive uncertainty of TOPMODEL using the Bayesian Generalized Likelihood Uncertainty Estimation (GLUE) methodology in an application to the small Ringelbach research catchment in the Vosges, France. The wide range of parameter sets giving acceptable simulations is demonstrated, and uncertainty bands are presented based on different likelihood measures. It is shown how the distributions of predicted discharges are non-Gaussian and vary in shape through time and with discharge. Updating of the likelihood weights using Bayes equation is demonstrated after each year of record and it is shown how the additional data can be evaluated in terms of the way they constrain the uncertainty bands. © American Geophysical Union 1996 IS - 7 JF - Water Resources Research EP - 2174 TI - Bayesian estimation of uncertainty in runoff prediction and the value of data: An application of the GLUE approach VL - 32 SP - 2161 KW - glue KW - hydrology KW - uncertainty AU - Freer, Jim AU - Beven, Keith AU - Ambroise, Bruno UR - http://www.agu.org/pubs/crossref/1996/96WR03723.shtml ER -