Volume 18, Issue 69 (fall 2014)                   JWSS 2014, 18(69): 215-225 | Back to browse issues page

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Nakhaei M, Amiri V. Estimation Variably Saturated Soil Hydraulic Parameters via Inverse Modeling and using Redistribution Experiment Data. JWSS. 2014; 18 (69) :215-225
URL: http://jstnar.iut.ac.ir/article-1-2875-en.html
Dept. of Applied Geology, Collage of Earth Sci., Kharazmi Univ., Tehran, Iran.
Abstract:   (7097 Views)

Modeling of flow and transport processes in variably saturated porous media requires detailed knowledge of the soil hydraulic properties. The hydraulic properties to be determined by the inverse problem solution are the unsaturated hydraulic conductivity K(h) and the water retention curve θ(h). The inverse modeling approach assumes that both θ(h) and K(h) as well as transport parameters can be determined simultaneously from transient flow data by numerical inversion of the governing flow and transport equations. In order to find answers to the questions of uniqueness, identifiability and stability of different experimental setups, a new numerical experiment of redistribution was carried out. To study the shape of the objective function near its minimum, response surfaces for the estimated parameters were generated. The sensitivity of model outputs with respect to changes in input parameters was also computed and analyzed. Results of the redistribution experiment suggest that the non-uniqueness increases when the model output variables are not sensitive enough to the optimized parameters. As expected, the estimated values of parameters were sensitive to the magnitude of error in the measured data. In this experiment, the parameter estimation based on the pressure head observations provides unique solution. Due to preferential flow in the sample, tensiometric observations may provide poor results for inverse problem solution. Taking into account information about saturated hydraulic conductivity, Ks improved the likelihood of uniqueness and reduced the errors in parameter estimation of the shape parameters (α, n). It was found that the sensitivity analysis could be a useful tool to design the optimal time and location distribution of experimental observations.

Full-Text [PDF 503 kb]   (1510 Downloads)    
Type of Study: Research | Subject: Ggeneral
Received: 2015/01/11 | Accepted: 2015/01/11 | Published: 2015/01/11

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