Statistical framework for assessing uncertainty in hydrological models
Article first published online: 29 JAN 2013
©2013. American Geophysical Union. All Rights Reserved.
Eos, Transactions American Geophysical Union
Volume 94, Issue 5, page 60, 29 January 2013
How to Cite
2013), Statistical framework for assessing uncertainty in hydrological models, Eos Trans. AGU, 94(5), 60.(
- Issue published online: 29 JAN 2013
- Article first published online: 29 JAN 2013
- Cited By
- Bayesian statistics;
- climate impacts;
- computational hydrology;
- hydrologic scaling;
- uncertainty assessment
For regional managers trying to make long-term investments in hydrological infrastructure, having a reliable forecast of how their watershed may evolve in a changing climate is a significant boon. To make a projection of the regional effects of climate change, researchers often use the calculations of a global general circulation model to determine a set of initial conditions—for either historical or future climes—which can then be used to run a regional hydrological model. Using this approach, uncertainty can arise from a number of sources, including from the difficulties of projecting climate change, from errors within either the general circulation model or the hydrological model, from uncertainty surrounding modeled parameterizations, or from data sampling errors.