Determination of Unsaturated Soil Hydraulic Properties From Transient Outflow Experiments Using Genetic Algorithms

Takeshita, Yuji; Nakazawa, Kimitaka; Fukuda, Daiki; Kohno, Iichiro

doi:10.2208/jscej.1999.624_191

Cited by 13 publications

(11 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The algorithms used to find the “optimal” parameters may range from simple search algorithms that seek iterative improvement of the objective function starting from a single location in the search space [e.g., Ritter et al , 2003] to more advanced global search methods that utilize the strength of a population of individuals to efficiently search the space of potential solutions and avoid getting stuck in a local minimum of the objective function. Global optimization methods that have been used for the estimation of the unsaturated soil hydraulic properties include the annealing‐simplex method [ Pan and Wu , 1998], genetic algorithms [ Takeshita , 1999], multilevel grid sampling strategies [ Abbaspour et al , 2001; Lambot et al , 2002], ant colony optimization [ Abbaspour et al , 2001], and shuffled complex methods [ Vrugt and Bouten , 2002; Mertens et al , 2004, 2005, 2006]. Recent extensions include multiobjective search methods [e.g., Vrugt et al , 2003; Vrugt and Dane , 2005; Mertens et al , 2006], and simultaneous multimethod genetically adaptive optimization algorithms [ Vrugt and Robinson , 2007; Wöhling et al , 2008].…”

Section: Data Assimilation Methods For Estimating Vadose Zone Propertmentioning

confidence: 99%

On the value of soil moisture measurements in vadose zone hydrology: A review

Vereecken

Huisman

Bogena

et al. 2008

Water Resources Research

594

472

View full text Add to dashboard Cite

[1] We explore and review the value of soil moisture measurements in vadose zone hydrology with a focus on the field and catchment scales. This review is motivated by the increasing ability to measure soil moisture with unprecedented spatial and temporal resolution across scales. We highlight and review the state of the art in using soil moisture measurements for (1) estimation of soil hydraulic properties, (2) quantification of water and energy fluxes, and (3) retrieval of spatial and temporal dynamics of soil moisture profiles. We argue for the urgent need to have access to field monitoring sites and databases that include detailed information about variability of hydrological fluxes and parameters, including their upscaled values. In addition, improved data assimilation methods are needed that fully exploit the information contained in soil moisture data. The development of novel upscaling methods for predicting effective moisture fluxes and disaggregation schemes toward integrating large-scale soil moisture measurements in hydrological models will increase the value of soil moisture measurements. Finally, we recognize a need to develop strategies that combine hydrogeophysical measurement techniques with remote sensing methods.

show abstract

Section: Data Assimilation Methods For Estimating Vadose Zone Propertmentioning

confidence: 99%

On the value of soil moisture measurements in vadose zone hydrology: A review

Vereecken

Huisman

Bogena

et al. 2008

Water Resources Research

594

472

View full text Add to dashboard Cite

show abstract

“…Only recently have more powerful optimization methods for the identification of soil hydraulic parameters begun to appear in the literature. These include the use of annealing simplex methods (Pan and Wu, 1998), genetic algorithms (Takeshita, 1999; Vrugt et al, 2001), grid sampling strategies (Abbaspour et al, 1997), and ant‐colony methods (Abbaspour et al, 2001). Notwithstanding their successful application, these global search algorithms are computationally very demanding, requiring a substantial number of model evaluations to converge to the global solution.…”

Section: Inverse Identification Of Soil Hydraulic Parametersmentioning

confidence: 99%

Toward Improved Identifiability of Soil Hydraulic Parameters: On the Selection of a Suitable Parametric Model

Vrugt

Bouten

Gupta

et al. 2003

Vadose Zone Journal

View full text Add to dashboard Cite

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.

show abstract

“…As stated by Šimůnek and van Genuchten (1996), however, local minima are hardly identifiable because they may not appear in the cross‐section planes. Global optimization algorithms such as shuffled complex evolution algorithm (Duan et al, 1992), annealing–simplex method (Pan and Wu, 1998) or genetic algorithms (Takeshita, 1999) can improve the robustness of the inverse solution. Nevertheless, these techniques provide the best parameter set without information on the reliability.…”

mentioning

confidence: 99%