TY - JOUR
T1 - Estimation Variably Saturated Soil Hydraulic Parameters via Inverse Modeling and using Redistribution Experiment Data
TT - تخمین پارامترهای هیدرولیکی خاکهای دارای اشباعشدگی متغیر بهروش مدل سازی معکوس و بهرهگیری از دادههای توزیع مجدد رطوبت
JF - JSTNAR
JO - JSTNAR
VL - 18
IS - 69
UR - http://jstnar.iut.ac.ir/article-1-2875-en.html
Y1 - 2014
SP - 215
EP - 225
KW - Parameter estimation
KW - Inverse solution
KW - Objective function
KW - Response surface.
N2 - 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.
M3
ER -