<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>An accurate representation of reality in numerical variably-saturated flow models requires reliable estimates of necessary model parameters. Inverse modeling seeks to estimate parameters such as the saturated and residual water contents, the saturated hydraulic conductivity, the shape parameters of the soil hydraulic functions, using easily attainable observations of actual or cumulative water fluxes, pressure heads, water contents, and concentrations. The inverse procedure usually combines the nonlinear least-squares-based (SSQ) parameter optimization method with a numerical solution of the variably-saturated flow and transport equations. The SSQ-based inverse method is however sensitive to outliers. A novel Squared ε-Insensitive Loss Function (SILF) approach is introduced in this study. The SILF approach is inspired by the ε-insensitive loss function proposed by <italic>Vapnik</italic> (1995). The objective function used in the SILF approach is similar to the least-squares objective function, except that it penalizes only for errors greater than a certain predefined acceptable error term ε. The SILF approach shows an improved performance over the SSQ approach in estimating the soil hydraulic parameters. Apart from providing robust estimates of the soil hydraulic parameters, the SILF approach also gives an approximation of the relative measurement error during sampling.</p></abstract>

An accurate representation of reality in numerical variably-saturated flow models requires reliable estimates of necessary model parameters. Inverse modeling seeks to estimate parameters such as the saturated and residual water contents, the saturated hydraulic conductivity, the shape parameters of the soil hydraulic functions, using easily attainable observations of actual or cumulative water fluxes, pressure heads, water contents, and concentrations. The inverse procedure usually combines the nonlinear least-squares-based (SSQ) parameter optimization method with a numerical solution of the variably-saturated flow and transport equations. The SSQ-based inverse method is however sensitive to outliers. A novel Squared ε-Insensitive Loss Function (SILF) approach is introduced in this study. The SILF approach is inspired by the ε-insensitive loss function proposed by Vapnik (1995). The objective function used in the SILF approach is similar to the least-squares objective function, except that it penalizes only for errors greater than a certain predefined acceptable error term ε. The SILF approach shows an improved performance over the SSQ approach in estimating the soil hydraulic parameters. Apart from providing robust estimates of the soil hydraulic parameters, the SILF approach also gives an approximation of the relative measurement error during sampling.

Inverse modeling of vadose zone flow processes using squared ε-insensitivity loss function

Agronomy and Soils Department, Auburn University, Auburn, AL-36832

Department of Ecoregion Science, Tokyo University of Agriculture and Technology, Fuchu, Tokyo

Department of Environmental Sciences, University of California Riverside, Riverside, CA

Department of Mechanical Engineering, COPPE/LTTC, Federal University of Rio de Janeiro, UFRJ, Rio de Janeiro, RJ CEP 21945-970, Brazil

Journal of Hydrology and Hydromechanics

An accurate representation of reality in numerical variably-saturated flow models requires reliable estimates of necessary model parameters. Inverse modeling...

Inverse modeling of vadose zone flow processes using squared ε-insensitivity loss function

Published Online: Aug 26, 2010

Page range: 188 - 200

DOI: https://doi.org/10.2478/v10098-010-0018-9

Keywords
vodou nenasýtená pôda, inverzný problém, necitlivostná stratová funkcia

This content is open access.

Inverse modeling of vadose zone flow processes using squared ε-insensitivity loss function

Published Online: Aug 26, 2010

Page range: 188 - 200

DOI: https://doi.org/10.2478/v10098-010-0018-9

Keywordsvodou nenasýtená pôda, inverzný problém, necitlivostná stratová funkcia

This content is open access.

Keywords
vodou nenasýtená pôda, inverzný problém, necitlivostná stratová funkcia