Uncertainty Analysis for Watershed Modeling Using Generalized Likelihood Uncertainty Estimation with Multiple Calibration Measures
Publication: Journal of Water Resources Planning and Management
Volume 134, Issue 2
Abstract
This study applied a generalized likelihood uncertainty estimation (GLUE) approach to a Hydrological Simulation Program—Fortran (HSPF) model used for the simulation of hydrology and transport of fecal coliform bacteria at Moore’s Creek, Va. The procedures of the GLUE application to Moore’s Creek HSPF model include: (1) a Latin hypercube sampling approach to generate multiple parameter sets from a prior specified parameter space; (2) utilization of multiple calibration measures to evaluate the performance of HSPF predictions associated with each parameter set and definition of acceptance criteria to select the acceptable parameter sets; (3) a fuzzy logic model to calculate the likelihood values of the acceptable parameter sets; and (4) estimation of the distributions and construction of the uncertainty bounds for HSPF flow and fecal coliform predictions. Among 50,000 randomly generated parameter sets, 381 parameter sets are accepted. These parameter sets can lead to various HSPF flow and fecal coliform simulations closely matching the observed data given the observation errors. The results suggest that the multiple acceptable parameter sets identified by GLUE provide a sound basis for decision makers to evaluate uncertain hydrologic and water quality responses to a potential watershed management option.
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Acknowledgments
This work was supported in part by funding from the Virginia Water Resources Research Center. The writers also thank the three anonymous reviewers for their constructive suggestions that improved this work.
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 134 • Issue 2 • March 2008
Pages: 97 - 106
Copyright
© 2008 ASCE.
History
Received: Jun 21, 2005
Accepted: Mar 16, 2007
Published online: Mar 1, 2008
Published in print: Mar 2008
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