Reducing uncertainty in predictions in ungauged basins by combining hydrologic indices regionalization and multiobjective optimization

Zhenxing Zhang, Thorsten Wagener, Patrick Reed, Rashi Bhushan

Research output: Contribution to journalArticle (Academic Journal)peer-review


Approaches to predictions in ungauged basins have so far mainly focused on a priori parameter estimates from physical watershed characteristics or on the regionalization of model parameters. Recent studies suggest that the regionalization of hydrologic indices (e.g., streamflow characteristics) provides an additional way to extrapolate information about the expected watershed response to ungauged locations for use in continuous watershed modeling. This study contributes a novel multiobjective framework for identifying behavioral parameter ensembles for ungauged basins using suites of regionalized hydrologic indices. The new formulation enables the use of multiobjective optimization algorithms for the identification of model ensembles for predictions in ungauged basins for the first time. Application of the new formulation to 30 watersheds located in England and Wales and comparison of the results with a Monte Carlo approach demonstrate that the new formulation will significantly advance our ability to reduce the uncertainty of predictions in ungauged basins.

Original languageEnglish
Article numberW00B04
Pages (from-to)-
Number of pages13
JournalWater Resources Research
Publication statusPublished - 18 Sep 2008

Cite this