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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.
Copyright 2002 by the American Geophysical Union.
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