Characterizing Climate Model Uncertainty Using an Informal Bayesian Framework: Application to the River Nile
Publication: Journal of Hydrologic Engineering
Volume 18, Issue 5
Abstract
Assessing climate change effects on water resources is the first step in preparing climate change adaptation measures. However, this is often clouded by the large range of uncertainty resulting from a long chain of modeling activities. Despite progress made to improve climate models, downscaling methods, and hydrological models, uncertainties will remain. This paper proposes a framework to propagate and quantify the uncertainty from the different sources that can be applied at the full cascade but focuses on the climate-modeling component, i.e., different climate models and emissions scenarios. This framework is based on the generalized likelihood uncertainty estimation (GLUE) methodology, which is widely used in the hydrologic community but has not been applied as such to climate impact modeling. This paper presents a preliminary application of the proposed framework to the flow of the main Nile at Dongola.
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Acknowledgments
This research has been financially supported by the UNESCO-IHE Partnership Research Fund (UPaRF) within the ACCION project (Adaptation to Climate Change Impact on the Nile River Basin). The paper has been improved on the basis of constructive comments from three anonymous reviewers.
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© 2013 American Society of Civil Engineers.
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Received: Sep 13, 2011
Accepted: May 22, 2012
Published online: May 24, 2012
Published in print: May 1, 2013
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