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WATER RESOURCES RESEARCH, VOL. 38, NO. 12, 1312, doi:10.1029/2001WR001118, 2002

Toward improved identifiability of hydrologic model parameters: The information content of experimental data

Jasper A. Vrugt

Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, Netherlands


Willem Bouten

Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, Netherlands


Hoshin V. Gupta

Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona, USA


Soroosh Sorooshian

Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona, USA


Abstract

We have developed a sequential optimization methodology, entitled the parameter identification method based on the localization of information (PIMLI) that increases information retrieval from the data by inferring the location and type of measurements that are most informative for the model parameters. The PIMLI approach merges the strengths of the generalized sensitivity analysis (GSA) method [ Spear and Hornberger, 1980 ], the Bayesian recursive estimation (BARE) algorithm [ Thiemann et al., 2001 ], and the Metropolis algorithm [ Metropolis et al., 1953 ]. Three case studies with increasing complexity are used to illustrate the usefulness and applicability of the PIMLI methodology. The first two case studies consider the identification of soil hydraulic parameters using soil water retention data and a transient multistep outflow experiment (MSO), whereas the third study involves the calibration of a conceptual rainfall-runoff model.

Published 21 December 2002.

Index Terms: 1860 Hydrology: Runoff and streamflow; 1875 Hydrology: Unsaturated zone.

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Citation: Vrugt, J. A., W. Bouten, H. V. Gupta, and S. Sorooshian (2002), Toward improved identifiability of hydrologic model parameters: The information content of experimental data, Water Resour. Res., 38(12), 1312, doi:10.1029/2001WR001118.