Open AccessToward Improved Identifiability of Soil Hydraulic Parameters: On the Selection of a Suitable Parametric Model
Author(s) -
Vrugt Jasper A.,
Bouten Willem,
Gupta Hoshin V.,
Hopmans Jan W.
Publication year - 2003
Publication title -
vadose zone journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.036
H-Index - 81
ISSN - 1539-1663
DOI - 10.2136/vzj2003.9800
Subject(s) - identifiability , parametric statistics , pedotransfer function , estimation theory , parameter space , model selection , algorithm , parametric model , range (aeronautics) , computer science , selection (genetic algorithm) , mathematical optimization , richards equation , mathematics , soil science , soil water , environmental science , statistics , hydraulic conductivity , engineering , artificial intelligence , aerospace engineering
We present a thorough identifiability analysis of the soil hydraulic parameters in the parametric models of Brooks and Corey (BC; Brooks and Corey, 1964), Mualem–van Genuchten (VG; van Genuchten, 1980), and Kosugi (KC; Kosugi, 1996, 1999) using the recently developed Shuffled Complex Evolution Metropolis (SCEM‐UA) algorithm (Vrugt et al., 2002b, and unpublished data). Because the SCEM‐UA algorithm globally thoroughly exploits the parameter space and therefore explicitly accounts for parameter interdependence and nonlinearity of the employed parametric models, the algorithm is suited to generate a useful description of parameter uncertainty and its antithesis, parameter identifiability. A set of measured water retention characteristics of the UNSODA database (Leij et al., 1996) spanning a wide range of soil textures and three transient laboratory outflow experiments with decreasing flow rates were used to illustrate that a parameter identifiability analysis facilitates the selection of an adequate parametric model structure and provides useful information about the limitations of a model. Moreover, results suggest that one should be especially careful in establishing pedotransfer functions without knowledge of the underlying posterior uncertainty associated with the soil hydraulic parameters using direct estimation methods.