TY - JOUR
T1 - Toward improved identifiability of hydrologic model parameters
T2 - The information content of experimental data
AU - Vrugt, Jasper A.
AU - Bouten, Willem
AU - Gupta, Hoshin V.
AU - Sorooshian, Soroosh
PY - 2002/12/1
Y1 - 2002/12/1
N2 - 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.
AB - 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.
KW - Identification most informative measurements
KW - Parameter estimation
KW - Rainfall-runoff modeling
KW - Soil hydraulic properties
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U2 - 10.1029/2001wr001118
DO - 10.1029/2001wr001118
M3 - Article
AN - SCOPUS:0036998958
SN - 0043-1397
VL - 38
SP - 48-1-48-13
JO - Water Resources Research
JF - Water Resources Research
IS - 12
ER -